The effects of caloric restriction on adipose tissue and metabolic health are sex- and age-dependent
Caloric restriction (CR) reduces the risk of age-related diseases in numerous species, including humans. CR’s metabolic effects, including decreased adiposity and improved insulin sensitivity, are important for its broader health benefits; however, the extent and basis of sex differences in CR’s health benefits are unknown. We found that 30% CR in young (3-month-old) male mice decreased fat mass and improved glucose tolerance and insulin sensitivity, whereas these effects were blunted or absent in young females. Females’ resistance to fat loss was associated with decreased lipolysis, energy expenditure and fatty acid oxidation, and increased postprandial lipogenesis, compared to males. The sex differences in glucose homeostasis were not associated with differential glucose uptake but with altered hepatic ceramide content and substrate metabolism: compared to CR males, CR females had lower TCA cycle activity and higher blood ketone concentrations, a marker of hepatic acetyl-CoA content. This suggests that males use hepatic acetyl-CoA for the TCA cycle whereas in females it accumulates, stimulating gluconeogenesis and limiting hypoglycaemia during CR. In aged mice (18-months old), when females are anoestrus, CR decreased fat mass and improved glucose homeostasis similarly in both sexes. Finally, in a cohort of overweight and obese humans, CR-induced fat loss was also sex- and age-dependent: younger females (<45 years) resisted fat loss compared to younger males while in older subjects (>45 years) this sex difference was absent. Collectively, these studies identify age-dependent sex differences in the metabolic effects of CR and highlight adipose tissue, the liver and oestrogen as key determinants of CR’s metabolic benefits. These findings have important implications for understanding the interplay between diet and health, and for maximising the benefits of CR in humans.
This manuscript breaks new ground in old soil; i.e. sex differences in mouse and human studies and one of the greatest challenges facing translational investigators is the remarkable difference in phenotypes by sex. Defining those differences has been relatively straightforward, but understanding the underlying basis for the phenotypic effects continues to be difficult. This paper demonstrates the sex-and age-dependent effects of calorie restriction on adipose tissue and body composition. It then goes further in describing the metabolic distinctions that arise between males and females. As such, this study will open up new opportunities to explore these sex differences and to test the hypothesis that estrogen in younger animals and humans may be at the center of these effects. Furthermore, it provides a basis for determining why weight loss may be difficult for some individuals with calorie-restricted diets.https://doi.org/10.7554/eLife.88080.sa0
Caloric restriction (CR) is a therapeutic nutritional intervention involving a sustained decrease in calorie intake whilst maintaining adequate nutrition. CR extends lifespan and reduces the risk of age-related diseases in numerous species, ranging from yeast to primates (Lin et al., 2002; Weindruch et al., 1986; Mattison et al., 2017). CR can have detrimental effects, including bone loss (Villareal et al., 2016) and increased susceptibility to infections (Speakman and Mitchell, 2011), and therefore it may not be suitable for all individuals; however, trials of CR in humans show numerous health benefits, including the prevention of cardiovascular disease, hypertension, obesity, type 2 diabetes, chronic inflammation, and risk of certain cancers (Most et al., 2017). Thus, the ability of CR to promote healthy ageing is now also recognised in humans. In addition to these health benefits, many effects of CR reflect evolutionary adaptations that confer a survival advantage during periods of food scarcity (Speakman and Mitchell, 2011). Establishing the extent and basis of CR’s effects may thereby reveal new knowledge of healthy ageing and the interplay between food, nutrition, and health.
A key contributor to the health benefits of CR is its impact on metabolic function. Ageing is characterised by hepatic insulin resistance, hyperinsulinaemia, and excessive accumulation of white adipose tissue (WAT), particularly visceral WAT (Barzilai et al., 1998; López-Otín et al., 2016; Mancuso and Bouchard, 2019). The latter is coupled with adipose dysfunction, whereby WAT becomes unable to meet the demands for safe lipid storage. This results in ectopic lipid accumulation in the liver and other tissues, contributing to insulin resistance and metabolic dysregulation (Barzilai et al., 1998; Mancuso and Bouchard, 2019). CR counteracts these effects, decreasing WAT mass, increasing fatty acid (FA) oxidation, preventing ectopic lipid deposition and enhancing insulin sensitivity and glucose tolerance (Speakman and Mitchell, 2011). Notably, studies in rodents show that removal of visceral WAT, independent of CR, is sufficient to prevent insulin resistance, improve glucose tolerance and increase lifespan (Gabriely et al., 2002; Muzumdar et al., 2008; Tran et al., 2008). Visceral WAT loss in humans is also strongly associated with CR’s metabolic benefits (Larson-Meyer et al., 2006). Thus, the ability of CR to decrease visceral WAT, and the resultant improvements in hepatic insulin sensitivity, are likely central to CR’s effects on metabolic function and healthy ageing.
This importance of adiposity and metabolic function raises the possibility of sex differences in the CR response. Indeed, it is now well established that metabolic homeostasis and adipose biology differ substantially between males and females (Mauvais-Jarvis, 2018; Oliva et al., 2020; Valencak et al., 2017; Maggi and Della Torre, 2018); however, most preclinical rodent studies have used males only (Prendergast et al., 2014), suggesting that much of the CR literature may have overlooked sex as a potential determinant of CR’s effects. Nevertheless, some clinical and preclinical CR studies from our lab and others have identified sexually dimorphic responses (Kane et al., 2018; Redman et al., 2007; Shi et al., 2007; Cawthorn et al., 2016), whereby males lose fat mass to a greater extent than females. Oestrogens underlie many metabolic sex differences (Mauvais-Jarvis, 2018; Della Torre et al., 2018), suggesting that oestrogen may contribute to females’ resistance to fat loss during CR. However, the extent and basis of sexual dimorphism in CR’s metabolic effects remains to be firmly established.
Herein, we first systematically review the CR literature to establish the degree to which sex has been overlooked a determinant of the CR response. To further elucidate the extent and basis of sex differences, we studied CR in male and female mice and humans at ages where oestrogen is physiologically active or absent. Together, our findings show that the CR field has largely overlooked sex differences and reveal that both mice and humans display age-dependent sexual dimorphism in the metabolic effects of CR.
Sex is routinely overlooked as a biological variable in the CR literature
One review of the recent CR literature found that most rodent studies use males only, with females typically used only to address female-specific experimental questions (Kane et al., 2018); however, the extent of this bias in earlier CR studies, and whether it applies to human CR research, has not been assessed. To address these issues, we first systematically quantified the use of males and females, and the consideration of sex as a biological variable, in mouse and human CR studies (Figure 1, Figure 1—figure supplement 1). We focused on research published since 2003, when the European Commission first highlighted the importance of addressing sex as a biological variable (Lee, 2018). We also excluded studies that necessarily focused on a single sex, such as those addressing effects of CR on female reproductive function, leaving only studies in which there is no scientific rationale for ignoring potential sexual dimorphism. We found that male-only studies predominated for mice, accounting for ~64% of all mouse CR studies since 2003 (Figure 1A, Figure 1—figure supplement 1B). This is consistent with previous analyses of the more-recent CR literature (Kane et al., 2018). Fewer than 20% of studies used females only, while around 7.3% combined males and females, suggesting an assumption that sex would not influence experimental outcomes. In contrast,~60% of human studies combined males and females, while ~23% used only females and ~12% only males (Figure 1C, Figure 1—figure supplement 1B). Strikingly, by the end of 2021, studies that included both sexes and analysed data with sex as a variable were in a minority for both mice (~3.4%) and humans (~4.5%) (Figure 1A and C). Moreover, the proportion of studies using each sex or combination of sexes has remained relatively constant since 2003 (Figure 1A and C). Thus, efforts to increase the consideration of sex in experimental design, as promoted by the European Commission (Lee, 2018), Canadian Institutes of Health Research (CIHR) and National Institutes of Health (NIH) (Johnson et al., 2014), appear to have had little impact on the field of CR research.
We next focused on the minority of studies that did consider sex in their experiments (‘M&F separate’) and that included analysis of metabolic parameters. We found that results in ~74% of mouse studies (Figure 1B) and ~62% of human studies (Figure 1D) indicated a sex difference in the CR response. Thus, sex differences have been described in the CR literature, but the continuing dearth of studies that include both sexes suggests that this issue continues to be overlooked in the CR field.
Females resist CR-induced weight loss and fat loss
To explore sex differences in the CR response, we assessed the effects of 30% CR, implemented from 9 to 15 weeks of age, in C57BL/6 J and C57BL/6 N mice. As expected, CR decreased body mass in both males and females (Figure 2A) but this effect was greater in males, with ANOVA confirming a significant sex-diet interaction. This sex difference in response to CR is particularly clear when body mass is presented relative to baseline, pre-CR levels (Figure 2B).
To determine how fat and lean mass contribute to these diet and sex effects, body composition was assessed weekly using time-domain nuclear magnetic resonance (TD-NMR; Figure 2C–F, Figure 2—figure supplement 1A–B). CR decreased fat and lean mass in males, whereas females maintained fat mass and lost only lean mass (Figure 2C–F). A significant sex-diet interaction was apparent for absolute fat mass (Figure 2C) and for fat mass relative to baseline (Figure 2D); the latter showed that CR decreased fat mass in males, whereas AL males and AL or CR females increased fat mass to a similar extent over the 6-week duration (Figure 2D). For lean mass, a significant sex-diet interaction occurred for absolute mass, with losses being greater in males than in females (Figure 2E). However, when compared to baseline lean mass, the CR vs AL effect was similar between the sexes, in part because AL females continued to increase lean mass over time (Figure 2F).
Given that these body composition changes coincide with changes in overall body mass, we also assessed fat and lean mass as % body mass. Males preferentially lost fat mass and preserved lean mass in response to CR, with % lean mass being greater in CR vs AL-fed males (Figure 2—figure supplement 1A–B). In contrast, diet did not alter % fat or % lean mass in females, indicating that changes in body composition were proportionate to the overall changes in body mass (Figure 2—figure supplement 1A–B).
To determine how these changes relate to regional adiposity, we measured adipose depot masses after 6 weeks of AL or CR diet (Figure 2G, Figure 2—figure supplement 1C, Figure 2—figure supplement 2A). We found that in males but not females CR decreased the absolute mass of gonadal (gWAT), inguinal (iWAT), mesenteric (mWAT), and perirenal (pWAT) WAT depots, as well as brown adipose tissue (BAT; Figure 2—figure supplement 1C). CR also tended to decrease the absolute mass of pericardial WAT (pcWAT) in males only (Figure 2—figure supplement 1C). To determine if these changes were proportionate to changes in overall body mass, we further analysed the mass of each adipose depot as % body mass (Figure 2G, Figure 2—figure supplement 2A). This showed that the significant sex-diet interaction persisted for gWAT, iWAT, mWAT and pWAT. CR did not affect % BAT mass in either sex, although % BAT mass was significantly greater in males than in females (Figure 2—figure supplement 2A). Thus, both in absolute terms and as % body mass, CR decreases WAT mass in males but not in females.
We next analysed the masses of other tissues to determine if this sex-dependent effect of CR is unique to WAT. CR significantly decreased the absolute mass of the liver, pancreas, kidneys, gastrocnemius muscle (gastroc), heart, spleen, and thymus (Figure 2—figure supplement 2B). Significant sex-diet effects were detected for the liver and kidney, with CR causing greater decreases in males than in females; however, for each of the other tissues the CR effect was similar between the sexes (Figure 2—figure supplement 2B). In contrast to these effects on absolute mass, CR did not significantly affect the relative masses of each of these tissues, nor did sex influence the CR effect (Figure 2—figure supplement 2C). This indicates that the absolute masses of these tissues decreased in proportion to the changes in overall body mass. One notable exception is the adrenal glands, the mass of which was increased with CR to a greater extent in males than in females (Figure 2—figure supplement 2B–C). Together, these data show that the sex differences in CR-induced loss of body mass and fat mass are driven primarily by decreased WAT mass in males, which females robustly resist.
Females resist adipocyte hypotrophy and lipolysis during CR
Differences in WAT mass can be driven by changes in adipocyte size and/or adipocyte number. Thus, given the marked sex differences in the effect of CR on WAT mass, we next investigated this effect at the level of adipocyte size (Figure 2H–I, Figure 2—figure supplement 3A–B). CR significantly decreased average adipocyte area in males but not in females, both for gWAT (Figure 2H–I) and for mWAT (Figure 2—figure supplement 3A–B). This suggests that females resist lipolysis during CR. Consistent with this, CR increased plasma NEFA concentrations in males but not in females (Figure 2J). To further assess adipocyte lipolysis, we analysed phosphorylation of hormone-sensitive lipase (HSL) in iWAT. CR stimulated HSL phosphorylation in males but not in females (Figure 2K–L, Figure 2—figure supplement 3C). Moreover, across both diets HSL phosphorylation was lower in females whereas total HSL was increased by CR in females only (Figure 2K–L, Figure 2—figure supplement 3C). Together, these observations show that females resist lipolysis during CR.
Females suppress energy expenditure and increase postprandial lipogenesis more than males during CR
We next investigated if altered energy expenditure also contributes to the sex differences in the CR response. To do so, we used indirect calorimetry to analyse mice during week 1 and week 3 of CR, corresponding to periods of weight loss and weight maintenance, respectively (Figure 2A). This revealed that CR decreased total energy expenditure in both sexes, with greater decreases occurring during week 3 compared to week 1, and during nighttime compared to daytime (Figure 3A–B). Notably, during week 1, CR females had lower daytime, nighttime, and total energy expenditure than CR males (Figure 3A–B), likely explaining females’ resistance to weight loss and fat loss during the first week of CR (Figure 2A–D). The daytime diet differences disappeared when normalised to lean body mass (Figure 3—figure supplement 1A), suggesting that they are driven primarily by the loss of lean mass and a consequent reduction in basal metabolic rate. In contrast, CR still decreased in nighttime and total energy expenditure even when normalised to lean body mass (Figure 3—figure supplement 1A). The relationship between lean mass and total energy expenditure (P, Slope) did not differ among the groups; however, the intercepts of the best-fit lines (P, Intercept) did differ significantly, both during week 1 (Figure 3C) and week 3 (Figure 3—figure supplement 1B). Thus, for a given lean body mass, CR-fed males and females had significantly lower energy expenditure than their AL-fed counterparts (Figure 3C, Figure 3—figure supplement 1B). In contrast to these decreases in energy expenditure, CR increased total and daytime physical activity in both sexes, with CR females having higher activity than CR males during week 1 (Figure 3—figure supplement 1C). Together, these data show that CR decreases energy expenditure more in females than in males, despite increasing physical activity, and that factors beyond decreased lean mass contribute to this CR effect.
We next analysed the respiratory exchange ratio (RER) to assess how diet and sex influence carbohydrate and lipid oxidation, and if these effects differ as CR progresses. In AL mice, RER peaked during the night, when most food consumption and physical activity occurs; in contrast, RER for CR mice peaked from 12.00 to 17.00 in the daytime, following provision of the daily ration of CR diet (Figure 3D–E; Figure 3—figure supplement 2A). The effects of CR on average daytime, night-time or total RER did not differ between the sexes (Figure 3E, Figure 3—figure supplement 2A); however, the dynamic changes in RER during these periods, and the strong influence of feeding and fasting on RER in the CR mice, make such average RER measurements difficult to interpret. Thus, we further investigated if RER in the postprandial and/or fasted states differs between CR males and females. Postprandial RER, calculated as the average RER from 12.00 to 17.00, exceeded 1 in both sexes (Figure 3D and F), indicating that CR mice use dietary carbohydrates for FA synthesis (Bruss et al., 2010). Notably, this postprandial RER was greater in females than in males, particularly during week 1 (Figure 3F). Fasting RER, calculated as the average from 04.00 to 09.00, was below 0.8 for both sexes, indicating preferential oxidation of lipids rather than carbohydrates during this fasted state (Figure 3—figure supplement 2B). Fasting RER was lower during week 1 than during week 3 of CR but, unlike for postprandial RER, no sex differences were observed (Figure 3—figure supplement 2B). This suggests that relative lipid oxidation is greater in the first week of CR and is similar in males and females. However, given that females have lower absolute energy expenditure, we hypothesised that they would also have lower absolute FA oxidation (Bruss et al., 2010). As shown in Figure 3G and Figure 3—figure supplement 2C, CR increased absolute FA oxidation in both sexes during week 1, but not during week 3. Across both timepoints there was a significant sex-diet interaction, with CR increasing FA oxidation more in males than females (Figure 3G). Together, these data show that females have greater postprandial FA synthesis and lower absolute FA oxidation than males, particularly during the first week of CR. This highlights further mechanisms through which females maintain fat mass during CR.
Females resist CR-induced improvements in glucose homeostasis
We next investigated if other metabolic effects of CR also differ between the sexes. We found that CR decreased blood glucose to a greater extent in males than in females (Figure 4A). Consistent with this, oral glucose tolerance tests (OGTT) revealed that CR improved glucose tolerance in both sexes, but this effect was greater in males (Figure 4B). These diet and sex effects were reflected by the OGTT total area under the curve (tAUC), calculated against 0 mM blood glucose; however, they were not apparent for the incremental AUC (iAUC), calculated against fasting blood glucose for each mouse (Figure 4C). This suggests that differences in fasting glucose are the main driver of CR-induced improvements in glucose tolerance and the sex differences therein.
To further assess the basis for these effects on glucose tolerance, we analysed plasma insulin during the OGTT. CR decreased plasma insulin in males but not in females, largely because AL females were already relatively hypoinsulinaemic (Figure 4D). Based on these blood glucose and insulin concentrations we calculated the homeostasis model assessment for insulin resistance (HOMA-IR) (Matthews et al., 1985) and the Matsuda Index of insulin sensitivity (Matsuda and DeFronzo, 1999). Here, a lower HOMA-IR score or a higher Matsuda index indicate increased insulin sensitivity. Across both sexes CR significantly decreased HOMA-IR and increased the Matsuda Index; however, within each sex the CR effect was significant for males only, indicating that females resist CR-induced improvements in insulin sensitivity (Figure 4E).
Time of CR feeding does not alter the sex differences in CR’s metabolic effects
Time of feeding can influence the metabolic effects of CR (Speakman and Mitchell, 2011; Zhang et al., 2019). Therefore, to test if our feeding regime influenced the observed sex differences, we studied a cohort of mice that received their daily ration of CR diet in the evening instead of the morning (Figure 2—figure supplement 4, Figure 4—figure supplement 1). Consistently, we found that the sex-dependent effect of CR on body mass, fat mass, lean mass and WAT mass was conserved (Figure 2—figure supplement 4A–H). Similarly, an OGTT revealed that the diet and sex effects on glucose homeostasis persisted (Figure 4—figure supplement 1A–B).
Sex differences in glucose homeostasis are not explained by differential glucose uptake
The basis for the sex differences in CR-improved glucose homeostasis was next investigated. We first used positron emission tomography-computed tomography (PET/CT) with 18F-fluorodeoxyglucose (18F-FDG) to assess glucose uptake in vivo (Figure 5, Figure 5—figure supplement 1). We focused on tissues with high basal and/or insulin-stimulated glucose uptake, including the heart, brain, skeletal muscle, BAT, WAT, bone, and the bone marrow (BM; Bartelt et al., 2017); the latter was also included because CR increases bone marrow adipose tissue (BMAT), another site of high basal glucose uptake (Suchacki et al., 2020).
Consistent with previous observations (Suchacki et al., 2020), we found that glucose uptake was highest in BAT, followed by the brain, bones, BM, the heart and skeletal muscle (Figure 5A–B, Figure 5—figure supplement 1A). However, CR did not stimulate glucose uptake in any of these tissues and decreased tibial glucose uptake (Figure 5A), including in the BMAT-enriched distal tibia (Figure 5—figure supplement 1A). Gamma counting further revealed no significant effect of CR in the gastrocnemius muscle, arm bones, liver, pancreas, spleen, or thymus (Figure 5C, Figure 5—figure supplement 1B); however, across both sexes, CR tended to increase glucose uptake in iWAT and gWAT and this effect was significant when assessed across all WAT depots (Figure 5C). CR also significantly increased glucose uptake in the kidneys (Figure 5C). Several sex differences were further detected, independent of diet. Thus, females had lower glucose uptake into gastrocnemius muscle and higher glucose uptake into BAT, the heart, gWAT, the humerus, the forearm and the kidneys (Figure 5A–C). Notably, however, sex did not significantly alter the effect of CR in any of the tissues assessed. Thus, the sexually dimorphic effects of CR on glucose homeostasis are not a result of CR increasing glucose disposal to a greater extent in males than in females.
CR exerts sexually dimorphic effects on hepatic sphingolipid content
The lack of CR-driven differences in peripheral uptake suggested that sex differences in glucose homeostasis relate instead to effects on hepatic insulin sensitivity and glucose production. Therefore, we next tested whether altered lipid storage, implicated in sex-dependent differences in hepatic glucose production (Della Torre et al., 2018), might contribute to the sexually dimorphic metabolic effects of CR. Because gross hepatic triglyceride content was not affected by diet or sex (Figure 6A), we undertook a more-detailed molecular investigation of lipid species that may underpin altered hepatic glucose regulation, focussing on sphingolipids (Petersen and Shulman, 2017; Chaurasia et al., 2019). Targeted lipidomics revealed that total ceramide content was significantly lower in females than in males but was not influenced by CR (Figure 6B); however, individual ceramide species were modulated by CR in a sex-dependent manner. Thus, 22:0 and 22:1 ceramides were lower in females than in males and were decreased by CR, with this diet effect being stronger in males (Figure 6B, Figure 6—figure supplement 1A). Conversely, 23:0 ceramides were greater in AL females than in AL males and were increased by CR in males only (Figure 6B); a similar pattern occurred for 14:0, 16:0, 18:0, 18:1, 20:1, 26:0, and 26:1 ceramides (Figure 6—figure supplement 1A).
Ceramides are generated from dihydroceramides (DHCs) and an elevated hepatic ceramide:DHC ratio promotes metabolic dysfunction and insulin resistance (Chaurasia et al., 2019; Apostolopoulou et al., 2020). Thus, we further analysed DHCs and the ceramide:DHC ratio as potential mediators of CR’s sexually dimorphic metabolic effects. As for total ceramides, total DHCs were lower in females than in males; however, unlike for total ceramides, CR increased total DHCs in males only (Figure 6C). Differential effects of sex and/or diet also occurred for the specific DHC species. A common pattern was for CR to increase DHC concentrations in males only, such that these were lowest in AL males but similar in CR males, CR females and AL females; this pattern occurred for 16:0, 18:0, 18:1, 20:0, 23:0, 24:0, and 24:1 DHC species (Figure 6C, Figure 6—figure supplement 1B). CR increased 14:0 DHCs in both sexes, albeit more strongly in males, and decreased 22:0 DHCs across both sexes (Figure 6C, Figure 6—figure supplement 1B). The overall ceramide:DHC ratio was decreased by CR in males but not in females (Figure 6C) and this also occurred for many of the individual species, including 16:0, 18:0, 20:0, 22:0, 22:1, 23:0, 24:0 and 24:1 (Figure 6—figure supplement 1B); however, unlike for the total ceramide:DHC ratio, the ratio for each of these species was highest in the AL males and significantly lower in females, such that CR males had a similar ratio to females on either diet (Figure 6—figure supplement 1B). Consistent with this, principal component analysis of these ceramide data identified AL males as the most distinct group, with CR males being more similar to females on either diet (Figure 6D).
Together, these data indicate that CR suppresses ceramide synthesis to a greater extent in males than in females, highlighting a potential mechanism for CR’s sexually dimorphic effects on glucose homeostasis.
CR exerts sexually dimorphic effects on hepatic gene expression and ketogenesis
To further investigate how hepatic function contributes to the sex differences in glucose homeostasis, we used RNA-seq to characterise the livers of AL and CR mice. Principal component analysis of this RNA-seq data identified AL males as the most transcriptionally distinct group, while CR males were more similar to AL or CR females (Figure 7A). Volcano plots further revealed the substantial effects of sex and diet on hepatic gene expression (Figure 7B, Figure 7—figure supplement 1A–B): hundreds of genes were differentially expressed between males and females within each diet group (Figure 7B, Figure 7—figure supplement 1B) and between AL and CR mice, both within and across the two sexes (Figure 7—figure supplement 1A–B). To assess the metabolic implications of these transcriptional differences, we first analysed the expression of transcripts that encode proteins associated with gluconeogenesis, glycolysis, or the TCA cycle. Few significant changes were detected for individual transcripts (Figure 7B, Figure 7—figure supplement 1A), and therefore we used gene set enrichment analysis (GSEA) to assess higher-level transcriptional changes associated with these and other relevant metabolic pathways (Figure 7C). Gluconeogenesis-related genes were significantly increased with CR in each sex, but, against our expectations, they were more highly expressed in males than in females during CR (Figure 7C). The greatest difference between CR males and CR females was for genes related to oxidative phosphorylation and the TCA cycle, which increased with CR in males but not in females (Figure 7C); this was also apparent from the distribution of individual TCA-related genes in the volcano plots (Figure 7B, Figure 7—figure supplement 1A). Glycolysis-related genes were also increased by CR, more so in males, whereas transcripts relevant to FA β-oxidation and FA biosynthesis were increased by CR in both sexes (Figure 7C, Figure 7—figure supplement 1C–D). These gene expression profiles support the following model (Figure 7D): during CR, both sexes increase FA β-oxidation to generate acetyl-CoA and this is supported by increased FA biosynthesis. Males, more than females, also increase glycolysis for acetyl-CoA production; however, males utilise the acetyl-CoA to support increased TCA cycle activity and oxidative phosphorylation, pathways that are not increased by CR in females. If so, females should have greater hepatic acetyl-CoA levels than males during CR. To test this, we measured plasma ketone concentrations, which are a biomarker for hepatic acetyl-CoA (Perry et al., 2017). Consistent with our model, plasma ketones were significantly higher in females than males, particularly during CR (Figure 7E). Hepatic acetyl-CoA stimulates gluconeogenesis by activating pyruvate carboxylase; thus, despite transcriptional profiles suggesting increased gluconeogenesis in males (Figure 7C), females’ higher levels of acetyl-CoA would be expected to cause greater stimulation of gluconeogenesis, thereby explaining why, compared to males, females are better at maintaining blood glucose during CR (Figure 7D).
Sex differences in CR’s metabolic effects are absent when CR is initiated in aged mice
Another intriguing finding from our RNA-seq data is that CR significantly stimulates oestrogen response pathways (Figure 7C). Thus, one possibility is that young females resist many of CR’s metabolic effects because their endogenous oestrogens cause them to remain relatively metabolically healthy, even on an AL diet (Forney et al., 2020; Chaix et al., 2021). To begin testing if endogenous oestrogens influence the CR response, we next investigated the effects of CR initiated in 18-month-old mice, when females are anoestrous (Gee et al., 1983). Unlike in young mice, CR decreased body mass and fat mass to a similar extent in aged males and females, while the decreases in lean mass were greater in aged females (Figure 8A–C). Consistent with this, CR’s effects on the masses of individual WAT depots did not differ between the sexes (Figure 8D, Figure 8—figure supplement 1A). Among non-adipose tissues CR significantly decreased pancreas mass only in aged females, but there were no sex differences in the effects of CR on the masses of other tissues (Figure 8—figure supplement 1B–C). Thus, unlike in young mice, aged males and females show a similar effect of CR on overall adiposity and this is driven predominantly by loss of WAT.
We then investigated CR’s effects on glucose homeostasis and insulin sensitivity. As shown in Figure 9A, in aged mice the ability of CR to decrease fasting blood glucose was not significantly influenced by sex. CR improved glucose tolerance to a similar extent in aged males and females, with tAUC but not iAUC being significantly decreased with CR (Figure 9B–C). The latter indicates that, as for young mice, CR improves glucose tolerance in aged mice primarily by decreasing fasting glucose. Despite no sex differences in glucose tolerance, both sex and diet decreased glucose-stimulated insulin secretion, with this being greatest in aged AL males and decreased by CR more so in males than in females (Figure 9D). Interestingly, a sex-diet effect was observed for HOMA-IR but not for the Matsuda Index (Figure 9E); this is similar to the effects observed in young mice (Figure 4E) and suggests that in aged mice there remain some sex differences in the relationship between plasma insulin and gluconeogenesis in the fasted state. However, overall, these studies demonstrate that sex differences in the metabolic effects of CR are highly age dependent, with CR being equally effective in aged males and females whereas young females resist these aspects of the CR response.
In humans CR-induced fat loss is sex- and age-dependent
Finally, we investigated if the metabolic effects of CR in humans are also sex- and age-dependent. To do so, we retrospectively analysed data from 42 overweight and obese men and women who participated in a weight loss study involving a 4-week CR intervention. As in young mice, body mass and fat-free (lean) mass decreased more so in males than in females, with males also showing a trend for greater fold-decreases in total fat mass (Figure 10A–F). When adjusted for age (Figure 10G), fold-change in body mass differed significantly between males and females (P, Intercept = 0.025). This demonstrates that overall weight loss is greater in males than females, independent of age. In contrast, the decreases in fat mass and fat-free mass were sex- and age-dependent. Thus, fat loss in younger individuals was greater in males than females but, with age, fat loss increased in females but diminished in males (Figure 10H) (P, Slope = 0.007). Conversely, the loss of fat-free mass in younger individuals was greater in females than in males and this relationship reversed in older individuals (Figure 10I). As for fat mass, the relationship between age and loss of fat-free mass differed significantly between the sexes (P, Slope = 0.0004). In contrast, the sex differences in loss of fat mass or fat-free mass were unrelated to fat mass or BMI at baseline (Figure 10—figure supplement 1).
These age-sex interactions were particularly apparent when the cohort was divided into younger and older groups (<45 vs>45 years of age), selected based on the age when females’ oestrogen levels begin to decline (Diaz Brinton, 2012). Total weight loss was greater in males than females regardless of age (Figure 10J), but only in the younger age group did males show greater fat loss than females (Figure 10K). Conversely, males’ greater loss of fat-free mass occurred only in the older age group (Figure 10L). Notably, a similar pattern of age-dependent fat loss was apparent for CR in young vs aged mice (Figure 10—figure supplement 2). Thus, our data demonstrate that the ability of CR to decrease body mass, fat mass and lean mass is sex- and age-dependent in both mice and humans.
Herein we aimed to determine the extent and basis of sex differences in the metabolic effects of CR. We reveal that 96.6% (mouse) and 95.7% (human) of published CR research overlooks potential sex differences, with most mouse studies using males only whereas most human studies combine data from males and females. We show that, in young mice, CR decreases fat mass and improves glucose homeostasis to a greater extent in males than in females, whereas these sex differences are blunted or absent when CR is initiated in old mice. Young CR females likely resist weight loss and fat loss by having lower energy expenditure, lipolysis and FA oxidation, and greater postprandial lipogenesis, than young CR males, The effects of CR on hepatic gene expression and sphingolipid content also differ between young male and female mice, highlighting the liver as a key mediator of CR’s sexually dimorphic metabolic effects. Finally, we reveal that humans also exhibit age-dependent sex differences in the CR response, with younger age groups showing greater fat loss in males than females whereas, with increasing age, CR-induced fat loss becomes similar between the sexes. Together, these data identify sex and age as factors that have a major influence on the metabolic health outcomes of CR.
Age-dependent sex differences in CR’s metabolic benefits
Our observation that young females resist overall weight loss during CR is consistent with some previous findings in mice (Shi et al., 2007; Cawthorn et al., 2016; Piotrowska et al., 2016), monkeys (Mattison et al., 2017), and humans (Musante, 1976; O’Neil et al., 1979; Mauriège et al., 1999; Wong et al., 2012; Azar et al., 2016; Das et al., 2017). Young females’ resistance to CR-induced fat loss has also been reported in mice (Shi et al., 2007; Cawthorn et al., 2016; Cawthorn et al., 2014; Dionne et al., 2016; Li et al., 2010) and humans (Redman et al., 2007; Mauriège et al., 1999; Leenen et al., 1993; Fontana et al., 2010; Evans et al., 2012); however, fewer studies have directly assessed sex differences in the effect of CR on glucose homeostasis and insulin sensitivity. Many studies have included males and females but did not sex-stratify their analyses, thereby overlooking the potential impact of sex on these important metabolic outcomes (Larson-Meyer et al., 2006; Kraus et al., 2019). Nevertheless, CR in monkeys and humans has been found to improve glucose homeostasis and insulin sensitivity more so in males than in females (Mattison et al., 2017; Wong et al., 2012), consistent with our findings in young mice.
Our observations fundamentally extend this previous research by demonstrating, for the first time, that these sex differences are age dependent. The novelty of this finding highlights that relatively few studies have investigated CR when initiated in aged subjects. In 2004, Dhahbi et al showed that CR’s health benefits persist even when initiated in aged mice (Dhahbi et al., 2004), and subsequent research has compared the metabolic effects of CR when implemented in young vs aged animals (Sheng et al., 2021; Rohrbach et al., 2007). Unfortunately, these studies did not include females, an oversight that has persisted in the CR field (Figure 1, Figure 1—figure supplement 1). Other notable research has comprehensively compared aged males and females, but only in the context of lifelong CR that was initiated in younger mice (Mitchell et al., 2016). Two recent studies have also highlighted age-dependent sex differences in the effects of methionine restriction or time-restricted feeding, but these dietary interventions were limited to young vs middle-aged mice (Forney et al., 2020; Chaix et al., 2021). The most relevant previous research is perhaps from Brandhorst et al, who observed significant visceral fat loss in female mice fed a ‘fasting-mimicking diet’ from 16 to 20.5 months of age (Brandhorst et al., 2015). While this is consistent with our observations in aged females (Figure 8, Figure 8—figure supplement 1), it is limited by having not assessed glucose homeostasis nor including male counterparts for direct comparison. Thus, our study is the first to compare CR when initiated in young or old males and females and to thereby identify age-dependent sex differences in CR’s metabolic effects.
Our findings have several implications for interpreting previous CR research. Although most studies show that young females resist overall weight loss and fat loss during CR, such sex differences have not been universally observed. For example, in young female rats some studies report that CR decreases body mass and/or fat mass to a similar extent in both sexes (Porter et al., 2004; Valle et al., 2005; Valle et al., 2007), while others find fat loss to be even greater in females than in males (Hill et al., 1986; Hill et al., 1985). CR-induced fat loss has also been noted in young female mice (Fenton et al., 2009; Varady et al., 2010; Harvey et al., 2013; Zgheib et al., 2014), albeit in studies that lack males for direct comparison. Several human studies also show no differences in total fat loss with CR, even in younger women who are unlikely to be menopausal (Wong et al., 2012; Das et al., 2017; Janssen and Ross, 1999). What are the reasons for these inconsistent results, and can they further inform the basis for sex differences in the CR response?
Considering our present findings, one possibility is that, even in younger subjects, age differences might have influenced the outcomes of these CR studies. Indeed, both Janssen et al and Das et al studied women who, while pre-menopausal, were significantly younger than their male counterparts (Das et al., 2017; Janssen and Ross, 1999). Given that males’ fat loss decreases as they get older (Figure 10H and K), this disparity could have undermined the ability of these studies to detect sex differences in fat loss. A related, broader issue is that much human CR research has studied females who are over 45 years old (Musante, 1976; Mauriège et al., 1999; Wong et al., 2012; Leenen et al., 1993; Evans et al., 2012; Wirth and Steinmetz, 1998; Parker et al., 2002; Weiss et al., 2006). This is important because it is the age at which oestrogen levels typically begin to decline (Diaz Brinton, 2012) and after which we demonstrate no sex differences in fat loss (Figure 10K). Thus, our findings underscore the importance of properly age-matching males and females, and ideally confirming menopausal status, if the response to CR is to be reliably assessed.
While age is clearly an important variable, many animal studies still find no resistance to fat loss in young females (Fenton et al., 2009; Varady et al., 2010; Harvey et al., 2013; Zgheib et al., 2014), even when appropriately age-matched to male counterparts (Porter et al., 2004; Valle et al., 2005; Valle et al., 2007; Hill et al., 1986; Hill et al., 1985). Therefore, other factors must also be influencing CR’s sexually dimorphic effects. One possibility is that males show a greater CR response because they are usually heavier and fatter than females at the onset of CR, and thus have more fat available to lose. Consistent with this ‘baseline adiposity’ hypothesis, during CR in rats Hill et al found total fat loss to be greater in young females than young males and, unlike in mice, pre-CR adiposity was greater in the females (Hill et al., 1986; Hill et al., 1985). Moreover, we show that sex differences in baseline adiposity become less pronounced with ageing, such that % fat mass is similar in aged male and female mice (Figure 8D). Therefore, this hypothesis could explain why CR decreases fat mass in the fatter, aged females, whereas young, leaner females resist this effect. However, three key points argue against this hypothesis. Firstly, we show that young females’ resistance to fat loss still occurs in obese and overweight humans, among whom % fat mass is greater in females than in males, irrespective of age (Figure 10—figure supplement 3). This is consistent with numerous previous studies of overweight or obese humans, in which CR causes more weight loss and/or fat loss in males than females (Redman et al., 2007; Musante, 1976; O’Neil et al., 1979; Mauriège et al., 1999; Wong et al., 2012; Azar et al., 2016; Leenen et al., 1993; Evans et al., 2012; Wirth and Steinmetz, 1998). Secondly, in our human study we show that the sex differences in loss of fat or fat-free mass are unrelated to baseline adiposity or BMI (Figure 10—figure supplement 1). Finally, in young, non-obese humans, sex differences in fat loss persist even after controlling for variation in baseline fat and body mass (Das et al., 2017). Thus, sex differences in the CR response are a not simply a consequence of baseline differences in these parameters.
A third possibility is that young females’ resistance to weight and fat loss can be overcome if the extent and/or duration of CR is great enough. Our CR protocol involves a 30% decrease in daily caloric intake over 6 weeks. In contrast, those studies reporting fat loss in young females typically used CR of a greater extent and/or duration. For example, Hill et al studied 60% CR for 11 weeks (Hill et al., 1986; Hill et al., 1985) while Valle et al used 40% CR for 14 weeks (Valle et al., 2005; Valle et al., 2007). Others have tested CR of a similar extent to our studies (20–30%) but for longer durations, ranging from 10 weeks to 6 months (Porter et al., 2004; Fenton et al., 2009; Harvey et al., 2013). It is now well established that the CR response is dose and duration dependent (Speakman and Mitchell, 2011; Cawthorn et al., 2016; Dionne et al., 2016; Mitchell et al., 2016; Chen et al., 2015; Zhu et al., 2004), with the former having been systematically investigated in male mice (Mitchell et al., 2015b; Mitchell et al., 2015a; Mitchell et al., 2017; Derous et al., 2018). Thus, a key goal for future studies will be to determine how sex and age influence these dose- and duration-dependent effects.
A final important consideration is the distinction between total versus regional adiposity. Indeed, the CALERIE trial finds no sex differences in the loss of total fat mass but does show that, compared to men, women resist loss of trunk fat during CR (Das et al., 2017). This is consistent with our data showing that fat loss in young male mice is greatest for the visceral depots (Figure 2G, Figure 2—figure supplement 1C, Figure 2—figure supplement 2A, Figure 2—figure supplement 4G), and with previous observations for CR in obese humans (Redman et al., 2007; Leenen et al., 1993; Evans et al., 2012; Wirth and Steinmetz, 1998). Some CR studies may therefore have failed to detect sex differences because they measured only total adiposity, missing out on possible site-specific differences (Wong et al., 2012; Ballor and Poehlman, 1994). Thus, any studies seeking to fully understand sex differences in CR’s metabolic effects, whether in preclinical models or in humans, should always aim to assess adiposity on both whole-body and regional levels.
Basis for young females’ resistance to weight loss and fat loss
Our studies also shed light on the mechanistic basis for these sex differences. Previous murine CR studies show that females decrease total energy expenditure more than males, possibly resulting from greater suppression of BAT activity (Shi et al., 2007; Valle et al., 2005; Valle et al., 2007). Consistent with this, we find that CR suppresses energy expenditure more in young females than in young males, at least during the first week of CR (Figure 3A–B). In contrast, CR males and females have similar energy expenditure at week 3 of CR (Figure 3A–B), similar to our previous findings at week 4 of CR (Suchacki et al., 2022). Consistent with this, BAT activity is similar between AL and CR mice after 6 weeks of CR (Figure 5). Therefore, if using indirect calorimetry to understand the CR response, it is important to ensure that the calorimetry analyses coincide with timepoints at which the relevant CR responses occur.
Another advance over our previous calorimetry studies (Suchacki et al., 2022) is that, by using the higher-sensitivity Promethion system, we were able to measure RER and thereby identify sex differences in lipid metabolism. We find that, compared to CR males, CR females have greater postprandial lipogenesis but lower FA oxidation and lipolysis. This confirms previous observations in male or female mice only (Bruss et al., 2010; Varady et al., 2010) but extends these earlier findings by demonstrating key sex differences in these effects. It is also like the situation in humans, in which CR enhances WAT lipolysis in both sexes and females resist this effect (Mauriège et al., 1999). Together, these differences in lipid metabolism likely explain why young females resist fat loss during CR. Whether ageing alters these sex differences in lipid metabolism remains to be determined.
A final consideration is how time of CR feeding influences energy homeostasis. In our morning-fed mice, CR decreases energy expenditure more at nighttime than in the day. In contrast, Dionne et al found that in nighttime-fed mice CR decreases energy expenditure in the day but not at night (Dionne et al., 2016). However, both we and Dionne et al show that CR decreases 24 hr energy expenditure, demonstrating that this overall CR effect occurs irrespective of time of feeding.
Importance of visceral fat loss for CR’s metabolic effects
These effects on fat mass and lipid metabolism likely contribute to young females’ resistance to improved glucose homeostasis during CR. Human studies have shown that inefficient WAT lipolysis is associated with impaired glucose metabolism in women (Arner et al., 2018) and that, during CR, decreased fat mass is linked to the improvements in insulin sensitivity (Larson-Meyer et al., 2006). Similarly, studies of CR or lipectomy in animal models suggest that visceral fat loss contributes to CR’s broader metabolic benefits (Barzilai et al., 1998; Gabriely et al., 2002; Muzumdar et al., 2008; Tran et al., 2008; Larson-Meyer et al., 2006). However, no previous research has investigated if this relationship between fat loss and insulin sensitisation differs between the sexes. Our work therefore supports and extends these previous studies by demonstrating that CR-induced fat loss coincides with improved glucose homeostasis and insulin sensitivity in males and aged females, whereas young females’ resist these metabolic effects.
The liver as a key driver of sex differences in glucose tolerance
Several of our findings highlight the importance of the liver as a key mediator of CR’s sexually dimorphic metabolic effects. Firstly, our PET/CT data show that CR improves glucose tolerance without any marked increases in peripheral glucose uptake (Figure 5). This includes the BMAT-rich distal tibia, suggesting that, although BMAT has high basal glucose uptake (Suchacki et al., 2020), increased BMAT glucose uptake is not required for improved glucose tolerance during CR. Moreover, although CR does increase glucose uptake in WAT and the kidneys, this effect does not differ between males and females and therefore is unlikely to explain the sex differences in glucose tolerance (Figure 5B). Together our data are consistent with human studies showing that, in the fasted state, CR does not affect overall glucose disposal (Gazdag et al., 1999; Johnson et al., 2016); however, CR enhances insulin-stimulated glucose uptake (Sequea et al., 2012) and it is possible that this effect differs between the sexes. Our second relevant finding is that, during an OGTT, CR decreases the tAUC but not the iAUC, highlighting decreases in fasting glucose, rather than insulin-stimulated glucose disposal, as the main driver of the improvements in glucose tolerance. Thirdly, we show that CR’s effects on hepatic gene expression differ between young male and female mice (Figure 7, Figure 7—figure supplement 1). These transcriptional differences suggest that, during CR, both sexes increase hepatic FA oxidation, but only males increase TCA cycle activity and oxidative phosphorylation (Figure 7B–C). Strikingly, females have higher plasma ketone concentrations, a marker of hepatic acetyl-CoA content (Perry et al., 2017). Based on these data, our model is that CR males utilise hepatic acetyl-CoA to support the TCA cycle and ATP generation via oxidative phosphorylation; in contrast, in CR females the hepatic acetyl-CoA accumulates, thereby stimulating pyruvate carboxylase and promoting gluconeogenesis (Figure 7D). Consequently, females are better at resisting hypoglycaemia during CR. As discussed below, future studies using metabolic tracers or related approaches will be important to further test these conclusions.
How is loss of visceral fat linked with these hepatic effects? Visceral adiposity is strongly associated with increased hepatic fat storage (Liu et al., 2021), and decreased liver fat coincides with improved insulin sensitivity during CR, both in rats and humans (Perry et al., 2018; Taylor et al., 2018). Moreover, young female mice resist the decreases in hepatic triglycerides following short-term fasting (Della Torre et al., 2018) and prolonged time-restricted feeding (Piotrowska et al., 2016). Therefore, we were surprised to find that CR does not affect hepatic triglyceride content in young mice of either sex (Figure 6A). This may be because our young AL controls are lean and healthy, and therefore already have livers that are not excessively fatty. In contrast, many of the previous studies investigated CR in animals or humans that are older and/or with type 2 diabetes (Piotrowska et al., 2016; Perry et al., 2018; Taylor et al., 2018), thereby increasing the baseline/control hepatic fat content. This would not explain why our findings differ to those of Della Torre et al, who studied fasting in young, healthy mice (Della Torre et al., 2018); however, it is perhaps unsurprising that our 6-week CR elicits different effects to those induced during shorter term fasting.
Our above observations are important because they show that CR can exert metabolic benefits without decreasing hepatic triglyceride content. In contrast, we find that effects on sphingolipids may play a role, with CR altering hepatic sphingolipid content more so in young males than in young females. Here, the effect of diet and/or sex depends on the sphingolipid species concerned (Figure 6; Figure 6—figure supplement 1). This is reminiscent of the findings of Norheim et al, who report sex differences in hepatic ceramide content in mice fed obesogenic diets (Norheim et al., 2018). They further showed that the relationship between ceramides, body fat and insulin sensitivity also differs between males and females, focussing on 16:0 ceramide (C16:0). Indeed, ceramides’ influence on insulin sensitivity depends on the ceramide species. For example, hepatic increases in C16:0 have been implicated with the development of obesity-associated insulin resistance (Chaurasia et al., 2019; Turpin et al., 2014; Raichur et al., 2014; Raichur et al., 2019). This is seemingly at odds with our finding that CR increases hepatic C16:0 in young males but not young females (Figure 6—figure supplement 1). Thus, unlike in obesity, increased hepatic C16:0 during CR appears to be associated with improvements in insulin sensitivity.
The rate of conversion of ceramides to DHCs may be a root cause of insulin resistance (Holland et al., 2007; Zhang et al., 2012). This underscores the concept that the ratio between each ceramide and DHC species may influence metabolic function more than the absolute values of either (Apostolopoulou et al., 2020). More research is needed to determine how specific ceramide and DHC species, and the ratios thereof, impact sex differences in the health benefits of CR. Despite these remaining questions, our work extends previous observations by revealing that CR’s hepatic effects are sexually dimorphic and that this contributes to the sex differences in glucose tolerance and insulin sensitivity.
Oestrogen as a modulator of the CR response
In many cases, young females’ resistance to the metabolic effects of CR is associated with them already being relatively metabolically healthy on an AL diet. For example, young AL females have lower visceral fat mass and are more glucose tolerant than AL males (Figures 2G and 4B–C), and are similar to CR males and females in terms of fasting insulin and HOMA-IR (Figure 4D–E). We also show that, for most sphingolipid species, the hepatic ceramide:DHC ratio is similar between AL females and CR mice of either sex (Figure 6—figure supplement 1C), while our RNA-seq data show that CR males are more similar to AL females than AL males (Figure 7A). These patterns suggest that the mechanisms through which CR decreases visceral adiposity, improves glucose tolerance and modulates sphingolipid metabolism are already at least partially active in young females, even on an AL diet.
This observation helps to clarify potential mechanisms for CR’s age-dependent sex differences. Sexual dimorphism in metabolic function typically results from sex hormones, with genetic factors and/or developmental programming also playing a role. For example, X-chromosome-linked genetic factors influence sex differences in adiposity independently of sex hormones or other secondary sexual characteristics (Mauvais-Jarvis et al., 2017; Link et al., 2020), while the developmental and neonatal environment causes sexually dimorphic metabolic programming (Dearden et al., 2018). However, it is unlikely that these developmental or genetic factors explain the sex differences we observe. Developmental programming is unlikely because the early life environment of our mice was the same for both sexes and was devoid of any adverse or stressful stimuli. Similarly, if X-linked genetic factors were responsible then the sex differences would be expected to persist in aged females, but they mostly do not. This leaves sex steroids as the likely mediator. Consistent with this, oestrogen is now well known to influence metabolic function and the fasting response (Mauvais-Jarvis, 2018; Della Torre et al., 2018), and many actions of oestrogens overlap with those central to the effects of CR (Shen et al., 2014; Wei and Huang, 2019; Gupte et al., 2015; Klinge, 2020). Indeed, our RNA-seq data show that CR activates oestrogen response pathways in males and females (Figure 7C), further suggesting commonalities in the effects of oestrogens and CR. Herein, we further show that the sex differences in CR’s metabolic effects are absent or greatly diminished when CR is initiated at 18 months of age, when C57BL/6 females are typically anoestrus (Gee et al., 1983; Diaz Brinton, 2012). Similarly, CR does decrease fat mass in young ovariectomised females (Wheatley et al., 2011), while oestrogen treatment protects male mice from obesity-induced insulin resistance (Dakin et al., 2015; Zhu et al., 2014). Therefore, we propose that young females resist the metabolic effects of CR because, through endogenous oestrogen action, they already have high activation of pathways that mediate CR’s metabolic effects.
Limitations and further considerations
Our study represents a significant advance in knowledge by revealing that age and sex have a substantial influence over the metabolic benefits of CR. This highlights the need for preclinical and human CR research to address these variables as key determinants of the CR response, a consideration that we show has been lacking in most CR research. We show that these sex differences occur on a systemic, physiological level and that they extend to cellular and molecular effects within adipose tissue and the liver, observations that identify potential mechanisms for the age-dependent sex differences; however, a general limitation of our study is that these mechanisms remain to be directly addressed. Specific limitations are as follows.
Firstly, we used a feeding regimen common in rodent CR studies, with mice receiving a single ration of diet in the morning. We found that the sex differences persisted when the daily ration was given in the evening, demonstrating that the sexual dimorphism is not specific to a morning-fed regimen. However, such single-ration protocols invoke extensive daily fasting, with mice typically consuming all of the food within ~2 hr (Acosta-Rodríguez et al., 2022; Acosta-Rodríguez et al., 2017). Therefore, they include elements of both CR and of intermittent fasting. Recent studies have shown that such prolonged daily fasting contributes to the metabolic benefits and lifespan extension associated with CR, at least in male mice (Acosta-Rodríguez et al., 2022; Pak et al., 2021; Mitchell et al., 2019). Thus, it will be interesting to determine if these beneficial effects of prolonged fasting, and not just CR per se, also differ between males and females.
Secondly, regarding insulin sensitivity and glucose homeostasis, it would be informative to use hyperinsulinaemic-euglycaemic clamps and labelled metabolic tracers to comprehensively assess systemic and hepatic insulin sensitivity and determine if, as we propose, the differences in glucose homeostasis relate primarily to effects on gluconeogenesis and hepatic acetyl-CoA metabolism.
Thirdly, the role of oestrogen remains to be directly tested. This could be done in mice through ovariectomy studies and/or manipulation of ERα activity. We have also tried to determine oestradiol concentrations in our mouse plasma samples using mass spectrometry, a method required for reliable assessment of sex steroid concentrations (Handelsman and Wartofsky, 2013). However, despite extensive mass spectrometry optimisation efforts, we have not yet been able to reliably measure oestradiol using the relatively small plasma volumes available. Related to this, in our human studies we were unable to confirm the menopausal status of the female participants. Other limitations of our human studies are that they were done only in overweight or obese individuals; included relatively few younger participants; and lacked analysis of regional adiposity (e.g. visceral versus subcutaneous adipose tissue). These limitations reflect that our human study was not originally designed to directly test the influence of age and sex, with the data instead analysed retrospectively to address this. Future human research must therefore prioritise assessment of menopausal status and regional adiposity, both in lean and overweight/obese subjects, if the outcomes of CR are to be fully interpreted.
A fourth limitation regards the underlying molecular mechanisms. Pathways implicated in mediating CR’s effects include activation of AMPK, SIRT, IGF-1 and FGF21, modulation of mitochondrial function and inhibition of mTOR (Speakman and Mitchell, 2011; Kane et al., 2018). Thus, genetic, pharmacological and/or other approaches to manipulate these candidate pathways could be used to further dissect the molecular mechanisms underlying CR’s age-dependent sexually dimorphic metabolic effects. Such approaches are a promising basis for future research.
Beyond these specific limitations, a broader question is whether other effects of CR also differ between males and females in this age-dependent manner. Some research suggests that CR’s effects on cardiovascular function and healthy ageing differ between males and females (Kane et al., 2016; Ferland et al., 2016; Austad and Bartke, 2015); however, given the dearth of CR studies that directly assess sex differences (Figure 1, Figure 1—figure supplement 1) there remains a critical need to determine how age and sex influence the many other outcomes of CR. This is important not only for understanding fundamental biology, but also if we are to translate the benefits of CR, or CR mimetics, to improve human health. For example, if younger women resist many of CR’s health benefits, should any CR-based intervention focus only on older women, who may be more responsive?
Finally, while it will be useful to understand the extent and basis for these sex differences, it is also important to consider their broader purpose. Adipose tissue profoundly influences female reproductive function, with adipose-secreted factors acting within the central nervous system to indicate if the body’s energy stores are sufficient to support reproduction (Bohler et al., 2010). The hormone leptin is the key adipose-derived factor that impacts the hypothalamic-pituitary-gonadal axis: if fat mass is too low, for example in anorexia nervosa or lipodystrophy, then leptin levels are also insufficient, resulting in decreased gonadotropin secretion and impaired reproductive capacity. Normal menses resumes in anorexic individuals who regain weight and fat mass, or in lipodystrophic individuals following leptin treatment (Bohler et al., 2010; Misra and Klibanski, 2014). Notably, we previously demonstrated that female mice resist hypoleptinaemia during CR (Cawthorn et al., 2016). Thus, we speculate that females resist fat loss during CR to preserve reproductive function. Given the tight interplay between adipose tissue and systemic metabolic homeostasis, such resistance to fat loss then has consequences for CR’s other metabolic effects. This evolutionary pressure to overcome periods of food scarcity would thereby have driven the divergence of the CR response in males and females, with implications for current efforts to exploit CR therapeutically to improve human health.
Materials and methods
Studies in C57BL/6NCrl and C57BL/6JCrl mice were approved by the University of Edinburgh Animal Welfare and Ethical Review Board and were done under project licenses granted by the UK Home Office. Mice were originally obtained from Charles River (UK) and then bred and aged in-house. They were housed on a 12 hr light/dark cycle in a specific-pathogen-free facility with free access to water and food, as indicated. Data herein are reported according to the ARRIVE guidelines (Percie du Sert et al., 2020); no checklist is provided, but key details are as follows. Differences in mouse cohorts are summarised in Table 1, along with the groups being compared and the experimental unit. The exact number of mice used is stated in the figure legends. Sample sizes for each cohort were determined by power calculations using G*Power software, with effect sizes based on pilot studies and/or previously published data for fat loss and improved glucose tolerance (the primary outcomes being tested) (Cawthorn et al., 2016; Cawthorn et al., 2014); to increase power, data for young mice are reported across multiple cohorts from at least four separate studies, each of which revealed the same sex differences in CR’s metabolic effects. Mice were randomly assigned to each diet. To minimise potential confounders, such as the order of treatments or measurements, mice were treated or analysed based on the order of their ID number, a variable randomly distributed across the experimental variables (diet and sex). Blinding was not possible during the in vivo experiments because the experimenter(s) can see, based on presence or absence of diet, which mice are AL and which are CR; however, data analysis was done in a blinded manner. Mice were excluded from the final analysis only if there were confounding technical issues or pathologies discovered at necropsy. Ten mice from the young study were excluded from the analysis of OGTT and necropsy tissue masses because of a technical issue during gavaging for the OGTT, which compromised their subsequent food intake. One mouse was excluded from PET/CT data analysis because it accidentally had two doses of FDG administered. One aged mouse was excluded because of developing confounding liver tumours. For some cohorts, specific tissues were not weighed at necropsy and therefore these mice have no data for these readouts. For further details, please see the Source Data files.
Mouse CR studiesRequest a detailed protocol
Before assigning to AL or CR diets, mice were housed individually between 8 and 9 weeks of age (for young mice) or 77–78 weeks of age (for old mice). During this time, mice were fed a control diet (Research Diets, D12450B) ad libitum and daily food intake was determined by weighing the food remaining in each cage each day. Following 1 week of single housing, all mice were randomly assigned to control diet (Research Diets D12450B, provided AL) or the CR diet (Research Diets D10012703, administered at 70% of the average daily AL diet consumption). This CR diet is formulated for iso-nutrition at 70% CR, ensuring that malnutrition is avoided. The evening-fed CR mice (Figure 3—figure supplement 1) were fed daily between 1800 and 1900, while all other CR mice were fed daily between 0900 and 1000. We find that CR mice consume their entire ration of diet within 2–3 hr of feeding, consistent with other CR studies (Acosta-Rodríguez et al., 2022; Acosta-Rodríguez et al., 2017). For the first 2 weeks of CR mice were monitored and weighed daily to ensure they did not lose more than 30% of their initial body mass. For the following 4 weeks of CR, body mass was recorded weekly. Mice were assessed non-invasively for body fat, lean mass, and free fluid weekly from weeks 0 to 6 using TD-NMR (Minispec LF90II; Bruker Optics, Billerica, MA, USA). Blood ketone concentrations were measured from weeks 0 to 4 using a GKI-Bluetooth Blood Glucose & Ketone Meter (Keto-Mojo Europe, Amsterdam, Netherlands). At necropsy, mice were humanely sacrificed via cervical dislocation and decapitation. Tissues were harvested, weighed, and stored either in 4% formalin or on dry ice. Tissues in formalin were fixed at 4 °C for 2–3 days before being washed and stored in DPBS (Life Technologies). Tissues on dry ice were stored at –80 °C prior to downstream analysis.
Human weight loss study – participantsRequest a detailed protocol
This study was done before pre-registration was a requirement for clinical trials. Herein, we retrospectively analysed the study outcomes to investigate if sex and/or age influence the CR response. Forty-five overweight and obese males and females; age 21-61y, Body Mass Index (BMI) 26–42 kg/m2, were recruited by newspaper advertisement to participate in a weight loss (WL) dietary intervention study. Thus, the participants were non-randomly selected individuals who were sufficiently motivated to actively respond to the request for volunteers. During recruitment, participants underwent a medical examination and their general practitioners were contacted to confirm medical suitability to participate in the study. Written, informed consent was obtained, and the study was reviewed by the NHS North of Scotland Research Ethics Service (ethics number 09 /S0801/80). Participants were informed that the study was funded by an external commercial sponsor but the company was not named, and all packaging of the food range was removed before distribution. Three participants withdrew for personal reasons therefore data for n=42 is presented throughout; participant characteristics are summarised in Table 2. No data points were excluded from the final analyses.
Human weight loss study – protocolRequest a detailed protocol
Participants were asked to attend the Human Nutrition Unit (HNU) at the Rowett Institute of Nutrition and Health (Aberdeen, UK) twice weekly to pick up food supplies. Participants had their basal energy requirements determined and each participant was then fed an individualised diet with a caloric content equivalent to 100% of their resting metabolic rate (Table 2). This approach was taken to standardise the diet to account for individual energy requirements and energy restriction. All required food, drinks and snacks were provided and the study dietician was present to answer any questions. Participants were provided with a diet guide whereby women were encouraged to consume no more than 6.3 MJ/d (1500 kcal) and men 8.4 MJ/d (2000 kcal). They were encouraged to consume 3 meals a day (breakfast, lunch and dinner) with a portion of protein at each meal, and 5 portions of fruit and vegetables, 2 portions of fats, 3 portions of milk and dairy and 4 portions of wholegrain bread, potatoes, and cereals each day. Participants completed a descriptive food diary every day to record what and when they ate. Participants ate ad libitum, choosing when and what to eat from their supplies. They completed a detailed 7d weighed dietary record during week 4 of the WL phase of the study, to compare eating habits with a baseline 7d weighed record they completed before the study started. Energy and nutrient intakes were calculated using the Windiets programme (Univation Ltd; The Robert Gordon University, Aberdeen, UK).
Human weight loss study – Measurement of body compositionRequest a detailed protocol
Before and after WL, at weeks 0 and 4 respectively, measurements of body composition were conducted under standardized conditions as described previously (Johnstone et al., 2005), with participants instructed to fast overnight (at least 10 h). Height was measured at the beginning of the study to the nearest 0.5 cm using a stadiometer (Holtain Ltd, Crymych, Dyfed, Wales). The body weight of the participants was measured at screening, during food provision days and on all test days, wearing a previously weighed dressing gown, to the nearest 100 g on a digital scale (DIGI DS-410, C.M.S. Weighing Equipment Ltd, London, UK). Fat mass (FM) and fat free mass (FFM) were measured with the use of air displacement whole-body plethysmography (BodPod Gold – Body Composition System, Cosmed, Italy) (Mccrory et al., 1995).
Indirect calorimetryRequest a detailed protocol
Male and female AL and CR mice were housed individually in Promethion CORE System cages (Sable Systems International, Las Vegas, USA) from 9 to 10 or 12–13 weeks of age, corresponding to weeks 0–1 (‘week 1’) or 2–3 (“week 3”) after beginning AL or CR feeding. At each timepoint, mice entered the cages around 11 am on day 1 and were housed for three nights (four days in total). Data herein are from the 48 h period between 7am on day 2 and 7am on day 4, to allow habituation to the new cages during day 1. Before and after Promethion housing, each mouse was weighed and body composition determined by TD-NMR. Measurements of energy expenditure, oxygen consumption, carbon dioxide production, and physical activity were analysed using ExpeData software according to the manufacturer’s instructions. FA oxidation was determined as described previously (Bruss et al., 2010).
Oral glucose tolerance tests (OGTT)Request a detailed protocol
Mice were given a half portion of food the night (6pm) prior to the metabolic challenge. At 12:00 pm on the day of the OGTT a basal blood sample was collected by venesection of the lateral tail vein into EDTA-coated capillary tubes (Microvette 16.444, Sarstedt, Leicester, UK) and the basal glucose levels was measured using a glucometer (OneTouch Verio IQ, LifeScan Inc, Zug, Switzerland). D-glucose (G8270, Sigma, Poole, UK) was then administered at 2 mg per g of body mass by oral gavage of a 25% (w/v) solution. At 15, 30, 60, and 120 minut post-gavage, blood glucose was measured by a glucometer and tail vein blood was sampled in EDTA tubes, as for the basal (0 min) timepoint. Blood samples were kept on ice prior to isolation of plasma. Insulin was then measured in plasma samples by ELISA, following the manufacturer’s instructions (cat. #90080, ChrystalChem, Chicago, IL, USA). Insulin was converted from ng/ml to μU/mL by multiplying the ng/mL value by 28.7174 (based on mouse insulin molar mass of 5803.69). Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and Matsuda index were calculated as previously described (Matthews et al., 1985; Matsuda and DeFronzo, 1999).
PET/CT scanningRequest a detailed protocol
Immediately before and 15- and 60 min post 18F-FDG intraperitoneal injection, blood glucose was measured by tail venesection and blood was sampled directly into EDTA-microtubes (Sarstedt, Leicester, UK). At 60 min post 18F-FDG injection, mice were anaesthetised and 18F-FDG distribution was assessed by PET/CT scanning using a nanoScan PET/CT 122 S scanner (Mediso, Budapest, Hungary). Following the PET/CT scan, mice were sacrificed by overdose of anaesthetic (isoflurane), death was confirmed by cervical dislocation and tissues of interest were then dissected in a lead-shielded area. Half of each of the dissected tissues were snap frozen on dry ice or placed into 10% formalin. 18F-FDG uptake was then determined using a Wizzard2 gamma counter (PerkinElmer, USA) as previously described (Suchacki et al., 2020).
PET/CT analysisRequest a detailed protocol
PET/CT images were reconstructed and data analysed using PMOD version 3.806 (PMOD, Zurich, Switzerland). SUVs were calculated for regions of interest, namely BAT, iWAT, gWAT; heart; bone tissue (without BM) from tibiae, femurs, and humeri; To distinguish bone tissue from BM, a calibration curve was generated using HU obtained from the acquisition of a CT tissue equivalent material (TEM) phantom (CIRS, model 091) and mouse CT scans, as previously described (Suchacki et al., 2020).
Histology and adipocyte size quantificationRequest a detailed protocol
Dissected mouse tissue was fixed for 48 hr and paraffin embedded by the histology core at The University of Edinburgh’s Shared University Research Facilities (SuRF). Paraffin-embedded tissue sections were then sectioned at 100 µm intervals using a Leica RM2125 RTS microtome and collected onto 76x26 mm StarFrost 624 slides (VWR, UK). The slides were baked at 37 °C overnight before Haematoxylin and Eosin (H&E) staining. Quantification of adipocyte number and size was performed on H&E-stained adipose tissue using the ImageJ plug-in Adiposoft, an automated software for the analysis of adipose tissue cellularity in histological sections (Galarraga et al., 2012).
NEFA analysis in plasma samplesRequest a detailed protocol
NEFA standard solution (Wako, 270–77000) was serially diluted to concentrations of 2, 1.5, 1, 0.5, 0.25, and 0.125 mM. The standard dilutions, blank sample and plasma (2 μL) were pipetted into separate duplicate wells of a 96-well plate. Reagent 1 (200 μL) (Wako, 434–91795) was added to each well and the plate incubated at 37 °C for 5 min. Absorbance of each well was measured at 550 and 660 nm. Reagent 2 (100 μL; Wako, 436–91995) was then added to each well and the plate was incubated again at 37 °C for 5 min and absorbance measured at 550 and 660 nm. The 660 nm reading was subtracted from the 550 reading from both measurements and the mean blank absorbance subtracted from the mean duplicate absorbance from each sample. NEFA concentrations were then determined by regression analysis.
Protein isolation and western blottingRequest a detailed protocol
Frozen WAT samples were lysed in preheated SDS lysis buffer (1% sodium dodecyl sulfate (SDS), 0.06 M Tris pH 6.8, 12.7 mM ETDA, 1 mM PMSF, 1 mM sodium orthovanadate). After tissue disruption, the lysate was boiled at 95 °C on a dry heat block for 10 min. Boiled lysate was centrifuged at 16,000×g and the cleared liquid fraction below the lipid layer and above the pellet was removed to a new tube for downstream analyses. Protein concentration was quantified using the BCA protein assay (Pierce 23225). For SDS polyacrylamide gel electrophoresis, lysates were diluted to equal protein concentration in lysis buffer plus 4 X SDS loading buffer (4% SDS, 240 mM Tris-HCL ph6.8, 40% glycerol, 0.276%(w/v) beta-mercaptoethanol, 0.05% Bromophenol blue). Dithiothreitol was added to the lysates (25 mM final concentration). Samples were boiled for 5 min, cooled on ice for 1 min, vortexed, and equal amounts of protein (13 µg per lane) separated on gradient polyacrylamide gels (Bio-Rad, Hercules, CA, USA). Samples were then transferred to Immobilon-FL transfer membrane (Millipore, Billerica, MA, USA). After transfer, membranes were blocked in 5% milk for 1 hr at RT. Membranes were incubated in primary antibodies (Key resources table; each in 5% BSA) overnight at 4 °C, followed by incubation with secondary antibody (Key resources table) at 1:5000 dilution for 1 hr at RT. Fluorescent color was detected with Odyssey CLx Imager (LI-COR, Lincoln, NE, USA). Band signal was quantified using Image Studio v5.2 (LI-COR, Lincoln, NE, USA). Quantified data obtained from two different membranes were combined by using the strength of the signal of the ladder bands as a control for intensity differences between the two membranes.
Liver ceramide quantificationRequest a detailed protocol
Liver ceramide and dihydroceramide content was determined using LC-MS (Lipidomics Core Facility; University of the Highlands and the Islands, Inverness, UK). As per (Folch et al., 1957), 100 mg of frozen liver tissue was homogenised in ice-cold MeOH using a mechanical tissue homogeniser. Fifty microlitres of each sample was combined with 100 μL ceramide 17:0 (1 μM in MeOH) and 25 μL dihydroceramide 12:0 (2 μM in MeOH; Avanti Polar Lipids, Alabaster, AL, USA) as internal standards. MeOH (1.875 mL) and CHCl3 (4 mL) were added. Samples were then stored on ice for 1 hr with intermittent vortex mixing, centrifuged at 2000 rpm for 5 min at 4 °C and the supernatant was collected. KCl (0.9%; 1.45 mL per sample) was added to the supernatant and the samples were centrifuged at 2000 rpm for 5 min at 4 °C. The lower phase was collected and evaporated under nitrogen and reconstituted in 1 mL CHCl3. Solid phase extraction was performed via a 100 mg/3 mL Isolute silica column (Biotage, Uppsala, Sweden). The column was conditioned twice with 3 mL CHCl3 and then loaded with 1 mL of the sample. The bound sample was washed with 2 washes of 3 mL CHCl3 then eluted with 2 additions of ethylacetate CHCl3 (1:1 v/v). The collected eluate was evaporated and dried under vacuum and reconstituted in 200 μL MeOH. LC-MS/MS analyses were performed in positive ion mode on a Thermo TSQ Quantum Ultra triple quadrupole mass spectrometer equipped with a HESI probe and coupled to a Thermo Accela 1250 UHPLC system. The ceramides and dihydroceramides were separated on a Kinetex C8 HPLC column (1.7 μm; 100×2.1 mm; catalogue number 00D-4499-AN, Phenomenex, Macclesfield, UK). Mobile phase A was 90% H2O, 9.9% acetonitrile and 0.1% formic acid. Mobile phase B was 99.9% acetonitrile and 0.1% formic acid. The gradient was held at 80% mobile phase B for 1 min then gradually increased to 100% mobile phase B over 15 min. Mobile phase B at 100% was maintained for 1 min and then equilibrated to storage conditions. The flow rate used was 500 μL per min at 40 °C. Two µL of each sample was injected into the LC-MS/MS for ceramide analysis and 10 μL for dihydroceramide. Total ceramide and dihydroceramide concentrations were calculated from the summed concentrations of all the monitored molecular species. All values were normalised to wet weight of liver. Principal component analysis for ceramide and dihydroceramide data was done using RStudio (RStudio Team, USA), using the code provided (see ‘Data and code availability’, below).
RNA-seqRequest a detailed protocol
RNA was isolated from tissues using Ribozol solution (cat. No. N580, Amresco, USA,) according to the manufacturer’s protocol. RNA quantity and quality were quantified using a NanoDrop spectrophotometer (Thermo Fisher Scientific,USA) and RNA Integrity Number (RIN) was assessed using Agilent RNA 6000 Pico Kit and an Agilent 2100 bioanalyzer (Agilent, USA). Library preparation and sequencing was performed by BGI (Shenzhen, Guangdong, China); 100 bp pair-end sequencing was done using a DNBseq-G400 (MGI Tech). Calculations were done using Eddie Mark 3, the University of Edinburgh’s high-performance computing cluster. After the trimming by TrimGalore and quality control by FastQC, sequences were aligned to the mouse genome (mm10) with the annotation data from the website of University of California Santa Cruz (https://hgdownload.soe.ucsc.edu) using STAR (v2.7.10a) (Dobin et al., 2013). Mapped reads were counted using featureCounts in Subread package (v1.5.2) (Liao et al., 2014) and subsequent analyses performed using R, RStudio, GSEA, Enricher, and Morpheus. Count data were normalised and analysed using DESeq2 (v1.36.0) to detect differentially expressed genes (Love et al., 2014). Principal component analysis was performed using the prcomp function for 500 genes with the highest variation among samples after transforming the raw count data using the vst function from the DESeq2 package. R code used for the analysis are provided (see ‘Data and code availability”, below). For GSEA, a gene set collection including eight gene sets was used for Figure 7C; further details are in Table 3. Heatmaps were drawn with Morpheus.
Statistical analysisRequest a detailed protocol
Data were analysed for normal distribution using the Shapiro-Wilk normality test. Normally distributed data were analysed by ANOVA, mixed models or t-tests, as appropriate; mixed models were used for repeated-measures analyses in which some data points were missing or had to be excluded for some mice. Where data were not normally distributed, non-parametric tests were used. When appropriate, p values were adjusted for multiple comparisons. Data are presented as mean ± SEM or as Violin plots, as indicated in the figure legends. All statistical analyses were performed using Prism software (GraphPad, USA). A p-value<0.05 (after adjustment for multiple comparisons) was considered statistically significant.
All source data and code from which the figures are based is available through University of Edinburgh DataShare at https://doi.org/10.7488/ds/3758 under a Creative Commons Attribution (CC-BY) licence. Raw data from RNA sequencing have been depositied at NCBI's GEO repository with accession number GSE230402.
NCBI Gene Expression OmnibusID GSE230402. Sex differences in the effects of caloric restriction (CR) on hepatic gene expression in mice.
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Mone ZaidiSenior and Reviewing Editor; Icahn School of Medicine at Mount Sinai, United States
In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.
[Editors' note: this paper was reviewed by Review Commons.]https://doi.org/10.7554/eLife.88080.sa1
General Statements [optional]
In this study we reveal that, in both mice and humans, the metabolic benefits of caloric restriction (CR) are sex- and age-dependent. Through a systematic review of the literature, we show that sex differences have been largely overlooked by previous CR research, a finding that Reviewer 1 highlights as “an important point”. Our results have critical implications for understanding the fundamental biology linking diet and health outcomes, as well as translational strategies to leverage the therapeutic benefits of CR in humans.
We thank the reviewers for their helpful appraisal of our manuscript, which Reviewer 2 highlights as “a very well written paper”. Reviewer 1 emphasised the translational relevance of our findings and commented on the “systematic” nature of our study. They noted that it “was well performed”, “is a valuable and important contribution to the field”, and “will elicit great interest in the scientific and public readership.” Indeed, the importance of sex as a biological variable was the focus of a recent news feature in Nature (https://www.nature.com/articles/d41586-022-02919-x), underscoring the timeliness and relevance of our findings.
We hope the Editorial Board will agree on the value and importance of our study, which we have further improved through the revisions described below.
Description of the revisions
We have addressed almost all the reviewers’ points through the revisions described in Section 3. In addition, we have conducted extensive new calorimetry studies using the Promethion CORE system, which is the highest-resolution system available for indirect calorimetry. These new data, along with our lipolysis analyses, explain why females resist weight loss and fat loss during caloric restriction.
Description of the revisions that have already been incorporated in the transferred manuscript
We have addressed all of the reviewers’ major comments, as follows:
A) The clinical part is definitely the weak spot in the study. I don't think that the data should be omitted, but the authors should be very careful in interpreting the data. Obvious limitations apply to this part, which need to be more directly addressed in the abstract and discussion. It feels like the data from the small-scale clinical trial is exaggerated.
The clinical study was conducted by Prof Alex Johnstone’s group at the Rowett Institute of Nutrition and Health, University of Aberdeen. Her group are experts in the study of dietary interventions for weight loss. The study was conducted to a high standard and therefore we have the utmost confidence in the conclusions drawn from our analysis of this data.
As we discuss in response to the reviewer’s other points below, the clinical study was primarily designed to address other outcomes and we analysed the data retrospectively to investigate if sex and age affect CR-induced weight and fat loss. This explains some of the limitations that the reviewer mentions, e.g. the relatively low numbers of younger males, and the focus on overweight and obese subjects. As requested, we have now addressed these limitations as follows:
i. Updated the abstract to clarify that the data are from overweight and obese subjects.
ii. Updated the results to emphasise that we did a retrospective analysis of CR in overweight and obese subjects (lines 447-448).
iii. Performed an additional ANCOVA analysis to test if baseline adiposity or BMI contribute to the sex differences in body mass, fat mass or fat-free mass (new Figure 10—figure supplement 1); see Reviewer 1 Major Point D below.
iv. Updated the ‘Limitations’ section of the Discussion to highlight the retrospective nature of the human study (lines 768-770).
v. Updated the Methods to again clarify the retrospective nature of the analysis (lines 865-867).
B) It is important to mention in the abstract and the discussion that the human data came from obese participants. This might well influence the findings from human data.
The human subjects were overweight or obese; this was previously stated in the methods section (line 867) and in the discussion (lines 554-556). To further clarify this, we now also mention it in the Abstract (line 62) and have reiterated it in the Discussion (line 766-767). Importantly, the fact that humans still show age-dependent sex differences in fat loss, even when overweight and obese, supports our conclusion that this age effect in mice is not simply a consequence of aged mice being fatter than younger mice. We refer to this as the ‘baseline adiposity’ hypothesis (lines 546-563 of the Discussion). In response to point D below, we have also analysed if the loss of fat mass or fat-free mass is influenced by adiposity or BMI at baseline (pre-CR). Our analyses show that neither of these parameters explain the sex differences in loss of fat mass or fat-free mass (see new Figure 10—figure supplement 1).
C) It is very important to calculate the % calorie restriction of the human participants achieved throughout the CR study. This is crucial information to compare it to other studies.
We have updated the Methods (lines 885-889) to explain the basis for the weight loss diet, as follows: “Participants had their basal energy requirements determined and each participant was then fed an individualised diet with a caloric content equivalent to 100% of their resting metabolic rate (Table 3). This approach was taken to standardise the diet to account for individual energy requirements and energy restriction.” We have also updated Table 3 to show the caloric intake for males and females. Note that RMR accounts for ~60-70% of total daily energy expenditure (TDEE) in adults (Martin et al., 2022), so the diet in our study would give a daily caloric deficit of around 30-40% from baseline TDEE.
D) Since there is quite a wide range in the BMIs of the participants, can the authors also stratify against BMI?
We have done this against both baseline BMI and against baseline fat mass (the latter to further test the ‘baseline adiposity’ hypothesis). We now present this data in Figure 10—figure supplement 1. We find that, in males but not in females, baseline BMI or fat mass are significantly associated with the changes in fat mass or fat-free mass: surprisingly, individuals with higher baseline fat mass or BMI show less fat loss and a greater loss of fat-free mass during CR. Importantly, males and females do not significantly differ in the relationships between baseline fat mass (or BMI) and loss of fat mass or fat-free mass. This further supports our conclusion that the sex differences in fat loss are unrelated to differences in baseline adiposity. We report this in lines 445-446 of the Results and lines 558-560 of the Discussion.
E) There is no mention of any pre-study registration online of the clinical part (e.g. clinicaltrials.gov). Was this done?
This study was done before pre-registration was a requirement for clinical trials. We retrospectively analysed the study data to investigate if sex and/or age influence the outcomes. In the updated manuscript we now state this on lines 865-867 of the Methods, as well as in the Results (line 447) and Discussion (lines 768-770).
F) In the methods section the authors write "Participants were informed that the study was funded by an external commercial sponsor…". This is important information, and this is not mentioned anywhere else in the paper. Can the authors clarify this point? A commercial sponsor would, in my view, qualify for a conflict of interest that needs to be mentioned.
We have updated the Declaration of Interests section to clarify this as follows: “The human weight loss study was funded by a food retailer; however, the company had no role in the data analysis, interpretation or conclusions presented in this paper.”
G) How did the authors determine the group sizes for the clinical part? I have some doubts about the sub-group sizes. It would be valuable information if the authors had a statistical analysis plan prior conducting the study. It appears a bit, like the sub-groups were chosen at random, to match findings of the mouse data. Otherwise, there should have been a better allocation within the sub-groups (especially age).
We agree that larger group sizes would have been preferable. This limitation reflects that the study was not originally designed to test age and sex effects on CR outcomes, but instead was analysed retrospectively to investigate the impact of these variables. As mentioned above, we have updated the text of the manuscript to highlight the retrospective nature of the analyses. In the Discussion, under ‘Limitations’, we also highlight the fact that relatively few younger subjects are included in the human study (line 767).
H) There's a big problem with the age stratification of the male participants in the clinical data. If I'm correct there are only 5 males <45 years. Although this looks intriguing, this can easily be a sampling problem.
As above, we agree on the limitation of having relatively few males in this <45 group. We used 45 years as the cut-off point because this is the age when, in women, oestrogen levels begin to decline (as was stated in lines 537-539 of the Discussion, and now reiterated in lines 464-465 of the Results). The key data are those for the ANCOVA analysis (Figure 10H; previously Figure 9H) showing that the influence of age on fat loss differs between males and females across all ages; hence, this is not simply an artefact of the <45 vs >45 groupings.
I) The applied protocol for CR in mice is known to provoke long fasting phases and probably elicits some effects through fasting alone, rather than the caloric deficit. There are some papers out addressing this (e.g. by deCabo, Lamming). The authors should not dismiss this fact and at least address it in their discussion. Also, given this fact, it would be thoughtful to include a database-search – not only regarding CR – but also regarding various types of intermittent fasting protocols in humans and animal studies (similar to what the authors did in the supplemental figure).
We agree on the importance of highlighting recent studies demonstrating that prolonged daily fasting contributes to the outcomes of typical ‘single-ration’ CR protocols. We have added a new paragraph to the Discussion to address this (Lines 742-751).
Regarding the second point, we feel that including a new literature search that addresses not only CR, but also intermittent fasting, is beyond the scope of the current manuscript. However, this is a very good idea and would be worth addressing in a future standalone review article. We have also updated our source data to include all data from our literature reviews, to help if other researchers wish to analyse according to fasting duration or other variables.
J) Did the authors monitor the eating time of the mice?
We have since done this in new cohorts of mice fed using the same CR protocol. We find that the mice consume their food within 2-3 hours, consistent with other CR studies. We have now mentioned this in the Methods section (lines 848-849).
K) While CR certainly has a lot of health benefits in rodents and humans, it should be advised to raise the cautious note that it may not be beneficial for everyone in the general population. For some groups of people and in some cases (e.g. infectious diseases, pregnancy) even CR with adequate nutritional intake of micro/macronutrients might be disadvantageous. This should be mentioned clearly, as the topic gets more and more "hyped" in public media and online.
We now highlight this important point in the opening paragraph of the introduction (lines 73-75).
L) There is no indication of how the authors dealt with missing data. Statistically this can be very important, especially in cases with a low number of data points.
In the Methods section we previously explained (lines 829-830 that “Mice were excluded from the final analysis only if there were confounding technical issues or pathologies discovered at necropsy).” No data had to be excluded from our human study and we have now stated this in the Methods (line 878). For analyses involving paired or repeated-measures data (e.g. time courses of body mass or blood glucose), if data points were missing or had to be excluded for some mice then we used mixed models for the statistical analysis. We have now updated this information in the ‘Statistical analysis’ section of the Methods (lines 1058-1060). Because of the large numbers of mice used in our studies, analyses remain sufficiently well powered even if some data points were missing or had to be excluded.
M) Key data from qPCR should be followed up by western blots or other means. If this was done and there was no effect, the authors should report this. Also, is there any evidence or the possibility to support these findings regarding pck1 and ppara in human samples?
We have now used RNA sequencing to comprehensively determine how CR and sex influence the hepatic transcriptome. These data are reported in new Figures 7 and Figure 7—figure supplement 1 of the revised manuscript. The data identify extensive sex differences in how CR alters hepatic function. Gene set enrichment analysis shows that CR stimulates oxidative phosphorylation and the TCA cycle in males but not in females, even though, in both sexes, there is increased fatty acid oxidation. Moreover, we find that plasma ketone concentrations, a marker of hepatic acetyl-CoA levels, are increased in females compared to males. Thus, our data suggest that CR males use hepatic acetyl-CoA to support the TCA cycle, whereas, in females, acetyl-CoA accumulates, thereby activating pyruvate carboxylase and stimulating gluconeogenesis. These new data substantially improve our manuscript and highlight unexpected sex differences that may underpin the metabolic and health benefits of CR.
Regarding effects of CR on PCK1 and PPARA expression in human liver samples, no human CR studies have taken liver biopsies for downstream molecular analysis. Recent studies of the GTEx database confirm that hepatic gene expression in humans is highly sexually dimorphic (Oliva et al., 2020). We checked PCK1 and PPARA in the GTEx database and found that, in the liver, each of these transcripts is expressed more highly in females than in males (https://www.gtexportal.org/home/gene/PCK1 and https://www.gtexportal.org/home/gene/PPARA). While this is the opposite to what we observe in our ad libitum mice (previous Figure 6A; data now superseded by the RNAseq data), it demonstrates that sex differences in these genes’ hepatic expression do occur in humans. The effect of CR on their hepatic expression, and whether this differs between males and females, remains to be addressed.
N): I think it would be very valuable to analyse the sex-differences in lipolysis directly in fat tissues. The authors concentrated on differences in hepatic mRNA profiles, but there's an obvious possibility and gap in their story.
We agree and have now analysed lipolysis in two ways: firstly, by measuring plasma non-esterified fatty acids (NEFA), and secondly by measuring phosphorylation of hormone-sensitive lipase (HSL) in adipose tissue. These data, shown in new Figures 2K-L and Figure 2—figure supplement 3C, confirm that, during caloric restriction, lipolysis is less active in females than in males, which likely contributes to females’ resistance to fat loss. In the Discussion we cite previous research identifying sex differences in adipose lipolysis and lipogenesis and explain how this data fits with our findings (lines 603-609).
O) Given the relatively low n and sometimes small effect sizes I fear that some of their findings won't be reproduced by other labs. Were the (mouse) data collected all at once in one cohort or did the authors pool data from different cohorts/repeats?
We presume the reviewer means ‘relatively high n’, as most of our mouse analyses used large group sizes. The mouse data were pooled from across multiple cohorts, with ANOVA confirming that the same sex-dependent CR effects were observed within each cohort. This reproducibility across multiple cohorts is a clear strength of our study because it demonstrates the robustness of our findings. Importantly, the sex differences in fat loss, weight loss and glucose homeostasis were still observed in our much-smaller cohort of evening-fed mice (Figure 2—figure supplement 4 and Figure 4—figure supplement 1; n = 5-6), demonstrating that large sample sizes are not needed for other researchers to detect these effects.
a) The discussion is very extensive, and I suggest compressing the information presented there to make it more easily readable.
We have removed some text that was more speculative, such as the paragraph discussing a possible role for ERalpha. Because of the improved indirect calorimetry analysis, we have also removed the paragraph, under “Limitations”, that explained the limitations of the previous calorimetry studies. We have also revised wording elsewhere to state things more succinctly. However, given the scope of our study we feel we cannot substantially cut down the Discussion without compromising the interpretation of our findings. We note the Reviewer two’s comment that “This is a very well written paper” and feel that attempting to compress the extensive information in the Discussion would compromise, rather than help, the readability.
b) There is some confusion present in the literature regarding the nomenclature of CR/fasting interventions. Recently some reviews have summarized the different forms (e.g. Longo Nature Aging, Hofer Embo Mol Med, …) and the authors should address this briefly. Especially the applied CR intervention in mice overlaps with intermittent fasting.
We have updated the Discussion (lines 742-751) to explain how our single-ration CR protocol also incurs a prolonged intermittent fast, and how this fast per se may contribute to metabolic effects.
e) What was the decision basis for stratifying the human data into < and >45 years?
We used 45 years as the cut-off point because this is the age when, in women, oestrogen levels begin to decline (this point was stated in lines 537-538 of the Discussion, and we now reiterate it in lines 464-465 of the Results).
f) The part on aging starting in Figure 7 comes quite surprising and it is not clearly linked to the data before. A suggestion here would be to smooth the transition in the text and the authors could again perform a literature search regarding age-of-onset for CR/fasting interventions in mice and humans.
We have added a sentence to smooth the transition to these studies (lines 415-416), linking the rationale to findings from the RNAseq data that is shown in the previous section. We had previously done a literature search to identify the age of onset of CR interventions in mice and humans. We summarise the findings of this search in lines 502-518 and 531-541 of the Discussion. We have also updated the source data so that it includes our review of the CR literature, allowing other researchers to interrogate this data.
g) At the first mention of HOMA and Matsuda indices, the effect direction should be put into physiological context.
We now mention this in lines 290-291 of the Results.
h) There is no mention of how the PCA analyses were conducted.
We have updated the Methods to explain that the PCA analyses were done using R. We have updated the source data to include the outputs from these analyses, as well as the underlying code. These data and code are now available here https://doi.org/10.7488/ds/3817.
i) Were the mice aged in-house in the authors' facility or bought pre-aged from a vendor? Is it known how they were raised? If bought pre-aged, were female and male animals comparable?
We bred and aged all mice in house. Males and females were littermates from across several cohorts. Therefore, there are no concerns about lack of comparability resulting from environmental differences.
j) Very minor note: I think that "focussed" has become very rarely used, even in British English. I don't know about the journal's language standards, but I would switch to the much more common "focused".
We have updated to ‘focused’ as requested.
k) Figure 6B/F (PCAs) should indicate the % difference of each dimension.
We have updated the figures (now Figure 6D) to show the % variance accounted for by each principal component; this has also been done for the RNAseq data in new Figure 7A. We have also updated the figure legends to specify this.
l) Limitations section: Maybe tone down on "world-leading mass spec facility". This sounds like an excuse and this statement is unsupported and doesn't add anything valuable to the section. Other limitations would include the low n, as mentioned above and the mono-centric fashion of the mouse and human experiments.
We have addressed these points as follows:
– Toned down the description of our mass spec facility (they are renowned for expertise in steroid hormone analysis, so we our original text was intended to highlight that our facility are not novices for this).
– Regarding the low n for some of the human groups, we now highlight this on line 767 of the Discussion.
– We have added a new paragraph to the Discussion (lines 742-751) explaining the limitations of our CR protocol, i.e. that includes elements of both CR and intermittent fasting.
Point 1: This is a very well written paper.
We thank the reviewer for this kind comment.
Point 2: Since the authors fed the animals in the morning, this is likely the reason for energy expenditure to be different in the CR vs ad lib groups. Although the authors do study the effects of night v day feeding and saw no change in the outcomes regarding weight, this fact I think should be mentioned somewhere. Also, figure 4A is expressed a W while all the other graphs are in kJ. I think it would be nice to see it all consistent.
Regarding the first point, we agree that time of feeding can influence when energy expenditure is altered, but most studies show that CR decreases overall energy expenditure regardless of time of feeding. For example, Dionne et al. studied the effects of CR on energy expenditure, administering the CR diet during the night phase (Dionne et al., 2016). They found that CR mice have lower energy expenditure in the day but not in the night (Figure 3C in their paper), which is the opposite to our findings (previous Figure 4C; new figures 3A-B). However, total energy expenditure in their study remains decreased with CR. This goes against the reviewer’s suggestion that feeding the animals in the morning “is likely the reason for energy expenditure to be different in the CR vs ad lib groups”. We have updated our manuscript (Lines 611-616) to clarify this.
Regarding the second point, in our new figure 3 we use consistent units (kcal, or kcal/h) for all energy expenditure data. The figure legend also reflects this.
Point 3: For all the graphs, can you make the CR groups bold and not filled as it is hard to see the lighter colours.
We have updated the graphs so that the CR groups are represented by solid lines, rather than dashed lines.
Point 4: I know many investigators use them, but I am not sure how relevant HOMA-IR and the Matsuda index are in mice since they were specifically designed for humans.
The issue of whether it is correct to use HOMA-IR and/or Matsuda index in mice is often debated in the metabolism field. Importantly, we are not using the absolute values for HOMA-IR or Matsuda in the same way that they are used in humans; instead, we are comparing the relative values between groups because these are still physiologically meaningful. We discussed this with Dr Sam Virtue, an expert in mouse metabolic phenotyping (Virtue and Vidal-Puig, 2021), who agrees on their usefulness in this way.
Point 5: Something also to note is the fact that all the glucose uptake data is under basal conditions. Just because there are no differences in the basal state does not mean that there are no differences after a meal/during an insulin stimulation. I think that this needs to be discussed and the muscle and fat not completely discounted as a player in the differences seen.
We agree that CR can enhance insulin-stimulated glucose uptake, but our OGTT data suggest that it is effects on fasting glucose, rather than insulin-stimulated glucose uptake, that contribute to the sex differences we observe. We have now updated the Discussion (lines 642-645) as follows, “CR enhances insulin-stimulated glucose uptake (83) and it is possible that this effect differs between the sexes. Our second relevant finding is that, during an OGTT, CR decreases the tAUC but not the iAUC, highlighting decreases in fasting glucose, rather than insulin-stimulated glucose disposal, as the main driver of the improvements in glucose tolerance.”
Description of analyses that authors prefer not to carry out
Major point I: … it would be thoughtful to include a database-search – not only regarding CR – but also regarding various types of intermittent fasting protocols in humans and animal studies (similar to what the authors did in the supplemental figure).
We feel that including a new literature search that addresses not only CR, but also intermittent fasting, is beyond the scope of the current manuscript. However, this is a very good idea and would be worth addressing in a future standalone review article. To assist with this, we have updated the source data to include all details of the literature review presented in Figure 1. The link to the source data is provided in the manuscript.
Minor point c: The order of the subpanels in Figure 9 (and other figures where B is below A and so on) is confusing. Please rearrange or indicate in a visual way which panels belong to each other.
We disagree that the order of subpanels in Figure 9 (now Figure 10) is confusing: the panels are clearly labelled, and we find it most logical to have the absolute values shown in the top row (panels A, C and E), with the corresponding graphs of fold changes shown beneath each of these (panels B, D and F). This allows the reader to quickly compare the absolute vs fold-change data for each readout. If we had panels A-C on the top row and D-F on the second row, then the connection between graphs 10C and 10D would be less clear and comparable.
Minor point d: Did the authors also measure cardiovascular (e.g. blood pressure) parameters? There is some evidence out there that there is an age/sex dependency during fasting/CR. This would be a nice add-on to the rather small clinical data here.
We did measure various cardiovascular parameters for our mice but find, unlike for the metabolic outcomes, these generally don’t show sex or age differences. In our human study we measured blood pressure and heart rate before starting CR and at weeks 3 and 4 post-CR. For this response to reviewers we have summarized these human data in Author response image 1. The data show that CR decreases blood pressure and heart rate in males and females (Author response image 1A-E). In the younger age group (<45 years) the decrease in systolic blood pressure is greater in females than in males (Author response image 1J) and the changes in heart rate over time also differ between the sexes, irrespective of age (Author response image 1F). However, unlike for the effects on fat mass or fat-free mass (now shown in Figure 10H-I; previously Figure 9), across all subjects ANCOVA reveals no age-sex interactions in these cardiovascular effects.
We have decided to not include these data in the current study because we feel it is already extensive and is focused on metabolic outcomes. We instead plan to report the cardiovascular outcomes (from both humans and mice) in a separate paper.
Dionne, D.A., Skovso, S., Templeman, N.M., Clee, S.M., and Johnson, J.D. (2016). Caloric Restriction Paradoxically Increases Adiposity in Mice With Genetically Reduced Insulin. Endocrinology 157, 2724-2734. 10.1210/en.2016-1102.
Martin, A., Fox, D., Murphy, C.A., Hofmann, H., and Koehler, K. (2022). Tissue losses and metabolic adaptations both contribute to the reduction in resting metabolic rate following weight loss. Int. J. Obes. 46, 1168-1175. 10.1038/s41366-022-01090-7.
Oliva, M., Muñoz-Aguirre, M., Kim-Hellmuth, S., Wucher, V., Gewirtz, A.D.H., Cotter, D.J., Parsana, P., Kasela, S., Balliu, B., Viñuela, A., et al. (2020). The impact of sex on gene expression across human tissues. Science 369, eaba3066. 10.1126/science.aba3066.
Virtue, S., and Vidal-Puig, A. (2021). GTTs and ITTs in mice: simple tests, complex answers. Nat Metab 3, 883-886. 10.1038/s42255-021-00414-7.https://doi.org/10.7554/eLife.88080.sa2
Article and author information
Medical Research Council (MR/M021394/1)
- William P Cawthorn
British Heart Foundation (RG/16/10/32375)
- Adriana AS Tavares
British Heart Foundation (FS/19/34/34354)
- Adriana AS Tavares
British Heart Foundation (4-year PhD studentship)
- Benjamin J Thomas
- Richard J Sulston
Takeda Science Foundation (Fellowship for Young Japanese MDs & PhDs Studying Abroad)
- Yoshiko M Ikushima
Japan Society for the Promotion of Science (JSPS Overseas Research Fellowship)
- Yoshiko M Ikushima
Japan Foundation for Applied Enzymology
- Yoshiko M Ikushima
University of Edinburgh (Chancellor’s Fellowship)
- William P Cawthorn
University of Edinburgh (PhD Studentship)
- Andrea Lovdel
Carnegie Trust for the Universities of Scotland (RIG007416)
- William P Cawthorn
Wellcome Trust (221295/Z/20/Z)
- Adriana AS Tavares
Chief Scientist Office of the Scottish Government Health Directorates (SCAF/17/02)
- Roland H Stimson
- Hiroshi Kobayashi
National Center for Global Health and Medicine (20A1010)
- Hiroshi Kobayashi
Scottish Government (RESAS Strategic Research Programme)
- Claire Fyfe
- Alexandra M Johnstone
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. For the purpose of Open Access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.
This work was supported by grants from the Medical Research Council (MR/M021394/1 to WPC), the British Heart Foundation (BHF) (RG/16/10/32375 and FS/19/34/34354 to AAST; 4 year BHF PhD Studentship to BJT and RJS), the Takeda Science Foundation (Fellowship for Young Japanese MDs & PhDs Studying Abroad, to YMI), the Japan Society for the Promotion of Science (JSPS Overseas Research Fellowship, to YMI), the Japan Foundation for Applied Enzymology (to YMI), the University of Edinburgh (Chancellor’s Fellowship to WPC; PhD Studentship to AL), the Carnegie Trust (RIG007416 to WPC), the Wellcome Trust (Technology Development Award 221295/Z/20/Z to AAST; Multi-user equipment grant 223818/Z/21/Z for the Promethion system), the Chief Scientist Office of the Scottish Government (SCAF/17/02 to RHS), KAKENHI grants from MEXT/JSPS (21K08431 to HK), and a grant from the National Center for Global Health and Medicine (20A1010 to HK). CF and AMJ gratefully acknowledge financial support from the Scottish Government as part of the RESAS Strategic Research Programme at the Rowett Institute, University of Aberdeen. We thank Ami Onishi for assistance with indirect calorimetry studies using the Promethion system, and the BHF for supporting Ami Onishi’s salary through the Centre for Research Excellence Award III (RE/18/5/34216). The BHF also provided funding towards establishment of the Edinburgh Preclinical PET/CT laboratory (RE/13/3/30183) and support of the 2018 Very Important Project (VIP) PET prize, for which we are grateful. Finally, we thank Dr Matthew Bennett (University of Edinburgh) for advice analysing RNA-seq data; Prof Robert Semple (University of Edinburgh) and Prof Ormond MacDougald (University of Michigan) for helpful advice to interpret our findings; Stefanie Fung (University of Edinburgh) for assistance isolating RNA for RNA-seq; Dr Hai-Bin Ruan (University of Minnesota Medical School) and Dr Eleonora Pagano (Pontifical Catholic University of Argentina) for kindly providing a full text of Ballor and Poehlman, 1994 study (Ballor and Poehlman, 1994), and all staff at Edinburgh Bioresearch & Veterinary Services for their superb technical support. Finally, this manuscript was written entirely by the authors and without any use of large language models.
Written, informed consent was obtained, and the study was reviewed by the NHS North of Scotland Research Ethics Service (ethics number 09/S0801/80).
Studies in C57BL/6NCrl and C57BL/6JCrl mice were approved by the University of Edinburgh Animal Welfare and Ethical Review Board and were done under project licenses granted by the UK Home Office (project license numbers 708617 and PP2299608).
Senior and Reviewing Editor
- Mone Zaidi, Icahn School of Medicine at Mount Sinai, United States
- Preprint posted: February 22, 2022 (view preprint)
- Received: March 24, 2023
- Accepted: March 26, 2023
- Accepted Manuscript published: April 25, 2023 (version 1)
- Version of Record published: May 9, 2023 (version 2)
© 2023, Suchacki, Thomas, Ikushima et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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Social touch constitutes a key component of human social relationships, although in some conditions with social dysfunction, such as autism, it can be perceived as unpleasant. We have previously shown that intranasal administration of oxytocin facilitates the pleasantness of social touch and activation of brain reward and social processing regions, although it is unclear if it influences responses to gentle stroking touch mediated by cutaneous C-touch fibers or pressure touch mediated by other types of fibers. Additionally, it is unclear whether endogenous oxytocin acts via direct entry into the brain or by increased peripheral blood concentrations.
In a randomized controlled design, we compared effects of intranasal (direct entry into the brain and increased peripheral concentrations) and oral (only peripheral increases) oxytocin on behavioral and neural responses to social touch targeting C-touch (gentle-stroking) or other (medium pressure without stroking) cutaneous receptors.
Although both types of touch were perceived as pleasant, intranasal and oral oxytocin equivalently enhanced pleasantness ratings and responses of reward, orbitofrontal cortex, and social processing, superior temporal sulcus, regions only to gentle-stroking not medium pressure touch. Furthermore, increased blood oxytocin concentrations predicted the pleasantness of gentle stroking touch. The specificity of neural effects of oxytocin on C-touch targeted gentle stroking touch were confirmed by time-course extraction and classification analysis.
Increased peripheral concentrations of oxytocin primarily modulate its behavioral and neural responses to gentle social touch mediated by C-touch fibers. Findings have potential implications for using oxytocin therapeutically in conditions where social touch is unpleasant.
Key Technological Projects of Guangdong Province grant 2018B030335001.
Clinical trial number:
- Biochemistry and Chemical Biology
Extracellular vesicles (EVs) are released by all cells into biofluids such as plasma. The separation of EVs from highly abundant free proteins and similarly sized lipoproteins remains technically challenging. We developed a digital ELISA assay based on Single Molecule Array (Simoa) technology for ApoB-100, the protein component of several lipoproteins. Combining this ApoB-100 assay with previously developed Simoa assays for albumin and three tetraspanin proteins found on EVs (Ter-Ovanesyan, Norman et al., 2021), we were able to measure the separation of EVs from both lipoproteins and free proteins. We used these five assays to compare EV separation from lipoproteins using size exclusion chromatography with resins containing different pore sizes. We also developed improved methods for EV isolation based on combining several types of chromatography resins in the same column. We present a simple approach to quantitatively measure the main impurities of EV isolation in plasma and apply this approach to develop novel methods for enriching EVs from human plasma. These methods will enable applications where high-purity EVs are required to both understand EV biology and profile EVs for biomarker discovery.